Understanding Sponsored Search: Core Elements of Keyword Advertising

Understanding Sponsored S earch This book addresses the underlying foundational elements, both theoretical and methodological, of sponsored search. As such, the contents are less affected by the ever-changing implementation aspects of technology. Rather than focusing on the how, this book examines what causes the how. Why do certain keywords work whereas others do not? Why does that ad work well when others that are similar do not? Why does a key phrase cost a given amount? Why do we measure what we do in keyword advertising? This book speaks to that curiosity to understand why we do what we do in sponsored search. The content flows through the major components of any sponsored-search effort, regardless of the underlying technology or client or product. The book addresses keywords, ads, consumers, pricing, competitors, analytics, branding, marketing, and advertising, integrating these separate components into an incorporated whole. The focus is on the critical elements, with ample illustrations, and with enough detail to lead the interested reader to further inquiry. Jim Jansen is an Associate Professor at the College of Information Science and Technology at The Pennsylvania State University. He has authored and coauthored more than 200 research publications, with articles appearing in a wide range of journals and conferences. He is the author of Understanding User-Web Interactions Via Web Analytics, coauthor of Web Search: Public Searching of the Web, and coeditor of Handbook of Research on Weblog Analysis. Jansen is a member of the editorial boards of eight international journals and serves on the research committee for the Search Engine Marketing Professional Organization (SEMPO). He has received several awards and honors, including an ACM Research Award and six application development awards, along with other writing, publishing, research, and leadership honors. He is also a Senior Fellow at the Pew Research Center with the Pew Internet and American Life Project.



Understanding Sponsored Search Core Elements of Keyword Advertising

Jim Jansen The Pennsylvania State University

cambridge university press Cambridge, New York, Melbourne, Madrid, Cape Town, Singapore, São Paulo, Delhi, Tokyo, Mexico City Cambridge University Press 32 Avenue of the Americas, New York, NY 10013-2473, USA www.cambridge.org Information on this title: www.cambridge.org/9781107628366 © Jim Jansen 2011 This publication is in copyright. Subject to statutory exception and to the provisions of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press. First published 2011 Printed in the United States of America A catalog record for this publication is available from the British Library. Library of Congress Cataloging in Publication Data Jansen, Bernard J. â•… Understanding sponsored search : core elements of keyword advertising / Jim Jansen. â•…â•… p.â•… cm. â•…Includes bibliographical references. â•…ISBN 978-1-107-01197-7 – ISBN 978-1-107-62836-6 (pbk.) â•…1.╇Internet advertising.â•… 2.╇Internet searching.â•… 3.╇ Keyword searching.â•… 4.╇Search engines.â•… 5.╇ Branding (Marketing)â•… 6.╇Consumer behavior.â•…I.╇Title. â•…HF6146.I58J37â•… 2011 â•… 659.144–dc22â•…â•…â•… 2011010612 ISBN 978-1-107-01197-7 Hardback ISBN 978-1-107-62836-6 Paperback Cambridge University Press has no responsibility for the persistence or accuracy of URLs for external or third-party Internet Web sites referred to in this publication and does not guarantee that any content on such Web sites is, or will remain, accurate or appropriate.

Contents

page vii

Preface Acknowledgments

xiii

Notes on Terminology

xvii

1╅ A Context for Sponsored Search�������������������������������������������������������������������� 1 2╅ Modeling the Process of Sponsored Search �������������������������������������������������� 9 3╅ Understanding Customer Intent for Keyphrase Selection ������������������������ 31 4╅ Sending Signals to the Customer with Ads�������������������������������������������������� 61 5╅ Understanding Consumer Behavior for Sponsored Search ���������������������� 85 6╅ BAM!: Branding, Advertising, and Marketing for Sponsored Search������������������������������������������������������������������������������������������������������������ 111 7╅ Sponsored-Search Analytics������������������������������������������������������������������������ 149 8╅ The Serious Game of Bidding on Keywords���������������������������������������������� 177 9╅ Bringing It All Together in a Framework of Sponsored Search�������������� 203 10╅ The Future of Sponsored Search���������������������������������������������������������������� 217 Glossary

229

Index

273

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Preface

Almost in the beginning was curiosity. Isaac Asimov, Asimov’s Guide to Science [1]

As Asimov mentions in his Guide to Science [1], curiosity may be a basic human attribute. It is a drive that compels us to learn, discover, describe, and understand the world around us. It is this compelling drive that has driven me to write this book on sponsored search. I’ve had the privilege of having many discussions with some top-notch, and often young, search engine marketing professionals from well-known online marketing firms, as well as professionals from lesser-known firms. I’m typically impressed (very impressed, actually) with their depth and breadth of knowledge about the mechanisms and tactics of sponsored search. Many times, they have provided interesting and perceptive insights on techniques for keyword selection, methods for composing ad copy, and other aspects of implementing keyword advertising campaigns. However, I have always sensed an underlying curiosity from these professionals, pointing to a possible knowledge absence, regarding the foundational and underlying elements of sponsored search. Why does one select certain keywords (other than that historically they seem to work)? Why does one choose particular terms for one’s ad copy (other than that historically they seem to work)? Why is this bidding process the way it is? Why look at certain metrics and not at others? In other words, why do we do what we do? This book is for those who are curious about such things. I am one of these people, as I am curious why things are the way they are with sponsored search, which is the process in which advertisers pay to have their advertisements appear on a search engine results page in response to a query from a searcher. Sponsored search is also commonly known as keyword advertising. There is also a great practical benefit in understanding the theoretical foundations of what one does. Doing something just because it worked in the past will generally produce good results€– until the context, situation, or environment changes. Then, all the historical data and results are of little value. However, an understanding of the vii

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theory and models of a given area provides us with continuity during turbulent times [2], as theory is more stable and enduring. Therefore, theory is of value to both the academic and the practitioner. Potpourri: As an academic researcher, I used to be amazed by the number of scholarly articles on advertising that would lament the rift that exists between academic advertising researchers and advertising practitioners. I used to be amazed, but no longer. There is typically little effort expended to ensure that academic research is impactful to practitioners. Unfortunately, this is true in many academic fields and will remain so until the reward system changes (i.e., from publication to impact). For the content in this book, nearly every chapter has been reviewed by both a researcher and a practitioner to increase the possibility that the material will be of value to both. Also, theory helps us avoid ultimate relativism, where each individual case is unique in terms of attributes and context. Theory aids in finding the generalities among these individual cases, highlighting the trends and commonalities. Theory helps us see the forest in the trees. The contents of this book address the underlying foundational elements, both theoretical and methodological, of sponsored search. As such, the contents are less affected by the ever-changing implementation aspects of technology. Rather than focusing on the how, we examine what causes the how. r
r
r
r


Why do certain keywords work whereas others do not? Why does that ad work well when others that are very similar do not? Why does that keyword cost a given amount? Why do we measure what we do?

This book speaks to that curiosity to understand why we do what we do in sponsored search. So, this is not a how-to book for pay-per-click, keyword advertising, or sponsoredsearch efforts. There are many such books, manuscripts, articles, Web sites, and blogs that address in great detail the mechanical aspects of implementation. Many are quite good and are a must-read for anyone in the profession. However, these publications are continually updated, as their half-life is generally short given the rapid pace of change in the interfaces and algorithms of advertising platforms and technology. The theory of sponsored search is more enduring because keyword advertising is a business of people. I’m of the belief that the Internet, Web, and search engines have changed (and are changing) people’s behaviors but have had little effect on people’s thinking, or more accurately, their cognitive processing of the world around them. People may now communicate faster, process information in smaller chunks, and buy products and services differently, along with many other changes in behaviors. The metaphors they

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use may have changed. However, I find it hard to believe that cognitive processing developed over millions of years has altered much at all. Therefore, many of the theoretical perspectives in this book deal with people. Sponsored search is a people venture, with informational and technical aspects. Potpourri: Although I do not believe that there has been any change in the way people think, I am open to the possibility. In fact, there is some evidence that we may have undergone a radical transformation in the way people think, although it appears to have had nothing to do with the Internet. What is the evidence of this change? In the last 20,000 or so years, the average size of the human brain has decreased by about 10 percent [3]. That’s right! Going by brain size, Cro-Magnon had the best brain-to-body ratio. Modern humans have less brain per body mass. This decrease in brain size began about the time that humans transitioned from hunter-gatherer cultures to agricultural communities. Researchers believe that this decrease in brain size is the result of the more complex social structure of humans, which reduces the need for aggression and other cognitive processes to survive in the wild. In others words, we domesticated ourselves! This domestication might have caused a smaller brain, which may have resulted in a change in the way humans think. It has been observed that domesticated animals (i.e., dogs, cats, sheep, cows, etc.) have smaller brains than their wild counterparts. However, the Internet appears to have had no effect on this reduction in human brain size, as far as we can tell. What is the relationship between theory and practice? There is an old academic joke that goes like this. “What is the difference between theory and practice?” The punch line is: “In theory, they aren’t that different. In practice, they are quite different.” (Note: Academic jokes typically are not particularly funny.) Like many jokes, it has an element of inherent truth. Theory and practice are different, as any account manager of a sponsored-search campaign will tell you. Every advertiser, every product, and every campaign has caveats and exceptions that the practitioner deals with on every account. However, there are some general trends, behaviors, and guidelines. Theory explains the principles and constructs underlying these guidelines and trends. Therefore, in this book, we deal with theories and models that have provided the grounding for the techniques that empirical testing and practice have shown to work – or not work – in sponsored search. The methods of practice are typically the result of repeated testing among many advertisers across many verticals. In this book, we aim to provide insight into these practices. We deal with the fundamentals that provide understanding. Do not, however, take away from this that I am against the empirical. Exactly the opposite, as I am an empirical researcher myself.

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Keyword advertising is, by nature, an empirical field. Many wonderful advertisers have been proponents of taking nothing at its face value, always testing [4, 5, 6, 7]. This is a position with which I completely agree. However, the theories presented in this book have withstood repeated empirical evaluation. They explain much of keyword advertising, although there are always caveats and exceptions for individual accounts, campaigns, keyphrases, and ads. Potpourri: Although some may consider theory the “higher ground,” I fully acknowledge that it all depends on the situation, and there are times when one can only solve a problem or leverage an opportunity via empirical research. One classic example of this is the invention of paper, with the credit going to Ts’ai Lun, around A.D. 105, although the word “paper” comes from papyrus, invented by the Egyptians, which was the first paper-like substance. The reason that paper is an empirical invention is that there is no “theory” that takes one from “I need a cheap, portable, durable, flexible, and versatile material to write on” to “therefore I need to pulverize wood, mix it with water, and let it dry.” One can only get from the need to the solution via empirical methods [8]. What subjects does this book not address? The book does not address affiliate marketing or contextual advertising in any great detail. These are forms of online advertising related to keyword advertising concepts, but they are distinct from the keyword-triggered advertising of sponsored search. Who is the book written for? The book is written for those interested in understanding the fundamentals of sponsored search, which includes: r
those just beginning in the sponsored-search area r
those who are skilled in the mechanics of keyword advertising The material presented here will be of great interest and value to those starting out in the area of sponsored search, providing a framework within which to connect the pieces inherent to this system. Such an introduction to the foundational elements can greatly accelerate the process of becoming skilled in this rather intricate area of online advertising. If this describes you to some degree, then this book is for you. From my own experiences, however, I believe that one must work in sponsored search for some time, becoming immersed in the subtleties, before one really understands its problems and issues. At this stage, one can only realize how nuanced the area is and how much there is still to learn. At such a point, a return to the foundational aspects is needed to reground oneself in the core concepts of the field. Otherwise, you get lost in the weeds! If this is generally your state of expertise, then this book is for you also. How do you read this book? The book is designed both to be a complete read and to serve as a reference for workshops, seminars, or courses. As a reference, one can use the whole book or individual chapters. I have attempted to be comprehensive, covering each of the major facets of sponsored search. So, depending on one’s background, there may be some areas

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with which one is not familiar. Each chapter is stand-alone. If there is a section that you do not understand fully, you can skip a chapter at first and then return later to reread. What academic fields are addressed? My focus is, of course, sponsored search, but I delve deep into the academic fields of information science, consumer behavior, and advertising, along with aspects of computer science, cognitive science, marketing, and statistics. However, I’ve avoided the nuanced jargon that academics favor and that is sometimes required when the precise meaning of a term is needed. Instead, I have sacrificed preciseness for an easier flow of content. Interested readers are welcome to dig deeper into the academic literature for the meticulous details. The chapters contain comprehensive references. In fact, I have attempted to provide published research to support common practices in the field. The book also has an extensive glossary of terms both addressed in the book and those one hears in the practice of sponsored search. So, although I focus on some weighty academic subjects, I have intentionally kept my writing light and conversational. There are some mathematical formulas, but these are accompanied by straightforward explanations. Each chapter contains selected items of interest (labeled Potpourri), a highlight of the major takeaways (if you like, you can read just these before wading into the whole book), and a subsection that relates the theoretical discussion to practice. The more experienced readers can certainly skip Chapter 1, which lays out the context of the rest of the book, although it is a short read and will not take much time. So, I encourage you to take the few minutes to read it. How is the book organized? I have partitioned the subject of sponsored search in rather precise chapters. I am not in favor of the books on Web subjects that come across as “random walks on the Internet” or “look at the Web pages that I browsed.” The separate chapters are somewhat artificially walled, but I have simultaneously attempted to integrate the chapters into a coherent whole. Therefore, although the chapters are stand-alone, the book is a consistent work. To make each chapter stand alone, there are a few instances where I must repeat a concept across multiple chapters. In these situations, I refer back to the chapter where the concept was introduced in full. Although this approach introduces some repetition, it also facilitates reader concentration on an individual chapter, without having to digest the entire book. As much as my academic nature will permit, I have attempted to keep the book short, direct, and to the point. However, at times, an aspect may be nuanced and require several examinations to drive the point home. Although the book is written in an easy-to-follow tone, I have taken great pains to ensure that every word counts. The downside of such an approach is that details and exceptions might not be given their fair due. However, other manuscripts and information sources are available that address these details and exceptions. Many of these sources are listed in the references. The content flows through the major components of any sponsored-search effort, regardless of the underlying technology or client or product. The book addresses keywords, ads, consumers, pricing, competitors, analytics, branding, marketing, and

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advertising, integrating these separate components into an incorporated whole. The focus is on the critical elements, with ample illustrations, and with enough detail to lead the interested reader to further inquiry. In sum, I have attempted to address the curiosity. The why. References [1] Asimov, I. 1965. “Chapter 1: What Is Science?” In Asimov’s Guide to Science. New York: Basic Books, pp. 3–16. [2] Shapiro, C. and Varian, H. R. 1999. Information Rules: A Strategic Guide to the Network Economy. Boston, MA: Harvard Business Press. [3] McAuliffe, K. 2010. “The Incredible Shrinking Brain.” Discover, September. pp. 54–59. [4] Caples, J. 1997. Tested Advertising Methods, 5 ed. Rev. by Fred E. Hahn. Upper Saddle River, NJ: Prentice Hall. [5] Hopkins, C. 1924. Scientific Advertising. New York: Cosimo Classics. [6] Ogilvy, D. 1963. Confessions of an Advertising Man. London: Atheneu. [7] Ogilvy, D. 1983. Ogilvy on Advertising. Toronto: John Wiley and Sons. [8] Hart, M. H. 1992. The 100: A Ranking of the Most Influential Persons in History. New York: Citadel Press.

Acknowledgments

Thanks! Merci! Danke! Spasibo! Gracias! Xie xie! Arigato! Dyakooyu!

There are many folks who have made this book possible and who deserve thanks and much more than the small token of appreciation that I offer here. Many of their efforts have made the content of this book clearer and sharper than my initial attempts and thus more valuable to readers. These folks deserve credit for their efforts and assistance, and I deeply appreciate their contributions: The kind folks at Cambridge University Press who were open to the idea and concept of this book, especially Lauren Cowles and David Jou. Both Lauren and David were just wonderful during the entire process. A big thanks also to the folks at Newgen Publishing and Data Services! Great job! The three anonymous reviewers of this book’s proposal who supported the concept of this book and provided initial feedback and guidance. Their quick response, enthusiastic encouragement, and wonderful suggestions were great early motivators for getting me started on this journey. Brooke Randell, independent copy writer, who performed expert proofing and content review of the entire book. Brooke was a former student of mine who has now moved on to better things! We’ll continue to hear more good things about her. Rianna Jansen, my daughter, who did the final copyediting prior to submission. She corrected the many mistakes of grammar that I interjected into the manuscript with my continual fiddling up to the last moment. Her efforts significantly improved the readability of the final content. Thanks also to the subject-matter experts who reviewed individual chapters. Nearly every chapter was reviewed by both an academic and a practitioner. The chapter reviewers were • • • • • •

Brad Geddes, CertifiedKnowledge.org Daehee Park, Acxiom Dietmar Wolfram, University of Wisconsin, Milwaukee Don Turnbull, independent consultant and researcher G. Allen Westra, Upper Iowa University George Michie, Rimm-Kaufamn Group xiii

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• • • • •

Acknowledgments

Lu Zhang, Penn State University Nico Brooks, Two Octobers Sebastien Lahaie, Yahoo! Research Shelby Thayer, Penn State University Theresa Clarke, James Madison University

I list the affiliations of the reviewers as a courtesy. However, the reviews provided were not the opinion of their respective institutions but only those of the individual reviewer. I thank Gord Hotchkiss and Ian Everdell, both of Mediative (formerly Enquiro), for the use of a search engine results page heat map for this book. Gord did one of the initial eye-tracking studies in the area. So, I am extremely thankful. My thanks to Clay Davis, who provided me with the idea for the Seven Words You Can’t Say on Television. I have interacted with many search engine marketing firms and agencies over the years, which added greatly to my understanding of the field of sponsored search and the techniques of keyword advertising. I’ve been fortunate to have a great relationship with IMPAQT, which has been a fantastic supporter of search engine marketing education. So, a special thanks to Richard Hagerty, IMPAQT CEO, who has truly been great! Thanks also are in order to the other search engine marketing and related agencies that have been gracious enough to give me their time, expertise, or assistance, which include: • • • • • • • • • • • • • • • • • • • • • • •

Acronym Media AskHowie.com Atlas Solutions (now part of Microsoft) bjTheory BlitzLocal Bloom Marketing CertifiedKnowledge.org ClickEquations Google AdWords Google Research GSI Commerce iProspect Mediative (formerly Enquiro) Pepperjam (now part of TrueAction) Razorfish Rimm-Kaufman Group Seer Interactive TrueAction (part of GSI Commerce) WebMasterWorld.com Wordstream Yahoo! Research Yahoo! Search Marketing Yodle

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Finally, I owe a big thanks to the many experts in the field of sponsored search, both academic and practitioner, with whom I have collaborated over the years in research, education, consulting, or expert witnessing. Your insights and knowledge have proven invaluable. Naturally, the errors, omissions, and mistakes contained in the pages of this book are mine and mine alone.

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Notes on Terminology

The investigation of the meaning of words is the beginning of education. Antisthenes, Greek philosopher of Athens, disciple of Socrates, 445–365 BC (attributed)

Within any complex field, such as sponsored search, that spans many domains of study, the jargon of the field can quickly become overloaded (i.e., the same term can have multiple meanings), inaccurate (i.e., a term can have nuanced meanings depending on the context, and the context may be different in a given case), and sloppy (i.e., several terms for the same thing or concept). Therefore, as Antisthenes reminds us, the study of words is at the foundation of education. In this book, I have striven to use the same term for the same concept throughout, to be as accurate as possible in discussion, and to be as precise as possible in usage of terminology. However, the nuances of meaning are often dependent on context and convention. Therefore, there are several issues of terminology that we must address. Searcher versus Potential Consumer • A searcher is a person who submits a query to a search engine, engages the results, or browses Web pages. • A potential consumer is a searcher who may make a purchase or is engaged in a possible e-commerce transaction. • A searcher engaged in a search process may at some point transition to be a potential consumer. The point of this transition is key to the concept of sponsored search. Consumer versus Potential Customer • A consumer is a person within a market segment. • A customer is a person who has a realistic possibility of converting (i.e., purchasing, signing up for a newsletter, etc.). • A consumer may at some point become a potential customer. In fact, this is the goal of sponsored search. xvii

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Keyphrase versus Keyword • A keyword is a word selected by an advertiser that links a searcher’s query to an advertisement. • A keyphrase is a set of two or more keywords. Keyword versus Term • A keyword is a word selected by an advertiser that links a searcher’s query to an advertisement. • A term is a word selected by a searcher for use in a query. • A query may contain one or more terms. Advertisement versus Sponsored-Search Result • An advertisement is a commercial message to a consumer. • A sponsored-search result is an advertisement that appears on a search engine results page. Search Engine as Business versus Search Engine as Technology • A search engine is a business, especially within the domain of sponsored search. • A search engine is a technology that provides a searching service, which can be a general-purpose search engine, a niche search engine, or a social media service that provides searching capabilities. • At times, one must view the search engine as a business and at other times as a technology. The viewpoint depends on the context of the discussion. Sponsored Search as Process versus Sponsored Search as Platform • Sponsored search is a process involving a search engine technology, the business aspect of the search engine as a company, a searcher who may become a potential customer, and an advertiser. • Sponsored search is a technology for advertising provided by a search engine. • Depending on the context, one must view sponsored search as a process and other times as a platform. The viewpoint depends on the context of the discussion. Advertiser versus Business • An advertiser is an entity that pays for a commercial message. • A business is an entity that can engage in advertising for some commercial purpose. • Sometimes, the advertiser and business can be the same entity. Business versus Organization • A business is an entity that can engage in advertising for some commercial purpose.

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• An organization is an entity that can engage in advertising for some noncommercial purpose. Advertiser versus Bidder • An advertiser is an entity that pays for a commercial message. • A bidder is an entity that engages in a sponsored-search auction. • Depending on the context, one must view an entity as an advertiser in the sponsored-search process and other times as a bidder in a sponsored-search auction. Search Engine as Auction Technology versus Search Engine as Auctioneer • A search engine provides a sponsored-search technology for advertising. • A search engine acts as an auctioneer in a sponsored-search auction. • Depending on the context, sometimes the search engine is the sponsored-search technology and other times the auctioneer. Its goals are different for each role. Rank versus Position • Rank is the numerical label for an advertisement in a sponsored-search listing. • Position is a slot for an advertisement in a sponsored-search listing. Keyphrase Bid versus Maximum Cost-Per-Click • A keyphrase bid is the amount that an advertiser is willing to pay to a search engine for serving its advertisement, typically for a click. • Maximum cost-per-click is the maximum amount that an advertiser pays for a click on an advertisement. • The maximum cost-per-click is equal to or less than the keyphrase bid. Sponsored-Search Effort versus Sponsored-Search Campaign • A sponsored-search effort is one or more sponsored-search campaigns by an advertiser. • A sponsored-search campaign is a set of keyphrases, bids, and advertisements cognitively linked to a topic by an advertiser. Web versus Internet • Web is a browser-based, typically HTTP and HTML communication medium, which is a layer of user application that sits on the Internet (note capital I) hardware and software network. • internet (note lowercase i) refers to any communication medium that is not browser-based, typically apps and software that facilitate user communication and transactions on the Internet (note capital I) hardware and software network.

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A Context for Sponsored Search

Context is the surroundings, circumstances, environment, background, or settings which determine, specify, or clarify the meaning of an event. Wiktionary, 2010 [1]

You must always consider the context within when a given phenomenon occurs to derive any meaning from it. As the Wiktionary quote states, the context is what clarifies the meaning of an event [1]. Let’s Place Ourselves in the Proper Context You are the owner of a small- to medium-size business that sells some product or service. Pick any product or service that interests you. We will use a framing shop as an example throughout this book. Our framing shop is called Faster Frames. You have a brick-and-mortar storefront, but you decide that you also want to sell your product (or service) online to better serve the potential customers in your immediate area and to potentially market to an audience beyond your specific geographical area. What do you do? Well, first you need some sort of virtual storefront. Traditionally, this has been a Web site, either built in-house or contracted out to a company that provides this service. However, it can also be a virtual presence on a number of social media platforms where some aspect of business occurs. For our framing shop, we have created a nice Web site showing our frames and our framing service. What now? It is rare for a brick-and-mortar store to have large numbers of potential customers just walk in. Most often, one has to do some marketing to alert the potential consumer base that the business exists. Certainly, if your product, pricing, performance, place, and people provide value to consumers, marketing is much easier, as your business will probably have a good brand image with the potential customer base. However, there are typically competing businesses that offer similar (or identical) products in one’s geographical area. So, even the top companies typically have to engage in some sort of marketing and advertising efforts. This is certainly true for our framing shop, as there are several national competitors, as well as numerous local franchises and several mom-and-pop stores. 1

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Understanding Sponsored Search

The situation is even more competitive in the virtual world. There could potentially be dozens, hundreds, even thousands of companies competing in the same market. You may even find that many of these companies have been competing with your brick-and-mortar store in your own geographical area. So whether you want to or not, you are competing in the online world! Given that framing is a service as well as a product, as long as we have a shipping and receiving service, there is no reason we cannot compete nationally for the high-end market. Each of these competing businesses has some sort of online presence, a virtual storefront. It is rare for a Web site to have large numbers of potential customers just randomly arrive at their site. Just as in the brick-and-mortar world, businesses must do some marketing to get new customers to their online storefronts. Certainly, given the competitive marketplace, this is true for our framing shop. Marketing on the Web hinges on a few key technology services. Social media sites are important as commercial marketing outlets and are especially important as viral marketing. However, the big marketing guns in the online world are the search engines. Of course, the social media sites and the search engines may be the same entities. How do these Search Engines Impact the Business? For years, search engines have been the major gateways to the Web. With their legions of software agents indexing Web pages, acres of computers for storing terms and metadata from these Web pages, and intuitive interfaces for searching, these search engines are the workhorses of the Web. They are critical navigational elements that enable people in their role as potential consumers (along with many other roles) to leverage the vast content on the Web. In other words, the major Web search engines are value enhancers. The information on these Web sites would be of little value if few people could find them. Potpourri: Although it is now obvious that search engines and the techniques they employ are critical tools for using the Web, it was not always so clear-cut. The original manuscript discussing the highly important Google ranking algorithm was rejected by the Special Interest Group on Information Retrieval (SIGIR) Conference, which is the leading information retrieval conference in academia. In defense of the SIGIR reviewers, the paper was not clearly written, which is an example of the important relationship between function and form. One cannot neglect either. A version of the paper was eventually published in an academic journal and has subsequently become one of the most highly cited papers in the informationretrieval field (see [2]). Why has the Web had such a big impact? One reason may be the theory of affordances [3], which posits that people view the world in terms of both object shapes (i.e., including spatial relationships) and object

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possibilities for action (i.e., affordances). This perception of object possibilities helps drive people’s action (i.e., perception drives action). Sometimes these affordances are what designers intended. At other times, people bring their own affordances to a technology, which has certainly occurred with the use of the Web. So for our virtual business, we have to get our Web site indexed by the major search engines. Luckily, this is fairly easy to do. Sometimes, we have to do nothing. Other times, we may have to request the search engine to index our site. Given that we are somewhat technically suave, we quickly get the Web site for our framing shop indexed by major search engines. Once indexed, though, our real challenge begins. The screen space on any computer or computing device is limited. There is only so much space (or screen real estate) to show information. So, when a searcher submits a query to a search engine, there are only so many results that a search engine can display. Let’s say this number of results is ten. Actually, ten is an exaggeration, as there are typically fewer than ten results that appear above the fold (the portion of the screen that first appears to the user where the user does not have to scroll down). Most users do not scroll down [4]. So, a potential customer submits a query that relates directly to your business. Although you might imagine that one of the results would be for your site, there is no guarantee. It is rare for a business to have a market alone to itself. Rather there may be from dozens to hundreds to thousands of businesses (all with viable products for the potential customer) competing for one of those ten result slots. Your business wants to be one of these ten slots on the first page of results, which is where most of the consumer traffic is; actually, you want to be at the top of this list. With each business equally viable, the search engine uses a variety of factors to rank which businesses get one of those ten slots. However, you have only a limited idea of what factors the search engine uses for ranking, so it is somewhat of a crapshoot. What other options does your business have to get on this page of results? One answer lies with sponsored search (a.k.a. keyword advertising, paid search, payper-click). Sponsored search is the process in which advertisers pay to have their advertisements appear on a search engine results page in response to a query from a searcher. In sponsored search, advertisers pay search engines for traffic from the search engine to their Web sites. With sponsored search, major Web search engines have significantly altered online commerce. Potpourri: Sponsored search can come in various forms; the most common is pay-per-click. The Search Engine Marketing Professional Organization (SEMPO) defines pay-per-click as a model of online advertising in which advertisers pay only for each click on their ads that directs searchers to a specified landing page on the advertiser’s Web site. Let’s say that our framing shop does not show up in the top ten for the query “frame shops” in our area. Then, we are really going to depend on sponsored search as an advertising medium.

4

Understanding Sponsored Search

How Do We Leverage Sponsored Search to Market Our Business? The major search engines have sponsored search platforms where one can establish an account within a short amount of time. There are a couple of implementations of sponsored search. We are going to assume that we signed up for the version where we pay the search engine when someone clicks on one of our ads (referred to as payper-click). We might sign up for accounts on multiple search engines. We sign up for a sponsored search account on a major search engine for our framing shop. Our goal in this sponsored search effort is the same as in all advertising endeavors. We aim to acquire new customers at a cost that permits us to make a profit on the products and services that we sell to these customers. Once Done with this Administration, What Do We Do? The first step is to select some words that we believe potential customers will use when they would want to find our business on the Web. Using the search engine’s sponsored search platform, we then add these keywords to our account. Typical keyphrases for our framing shop could be “frames,” “framing,” and “custom framing.” We decide what advertisements we want to appear when a searcher enters one of these keywords. Using the search engine’s sponsored search technology, we create the advertisements on our account, linking ads to the keywords that we selected. Let’s assume that we create the following ad for our framing shop: Faster Frame $50 Off Custom Framing Coupon FASTER FRAME Satisfaction Guaranteed www.fasterframe.com

Once we have a sponsored search account established and running, our ads can appear on Web pages, cell phones, tablets, and many other devices. These ads can take potential customers to our Web site or provide them a means to click the ad and call our business or visit some other site related to our business, such as one of our social media sites. Okay, How does the Search Engine Make Money? The search engine company does not provide this marketing service for free. We offer to pay the search engine a set amount for each keyphrase, which is called a bid. It is called a bid because there may be (and probably are) several other businesses wanting to show their ads for the same keywords that we want to show our ads. Each business offers a bid, and the laws of supply and demand take over. The more businesses that want to bid on a certain keyword, the higher the bid price to get your ads to show on the search engine results page (SERP), with the critical resource being screen real estate. The bid price is the maximum amount that we will pay the search engine when someone clicks on our ad. Generally, what we actually pay is the same as the bid price. Sometimes lower. Never higher.

A Context for Sponsored Search

5

This bidding process thus involves some decisions on the part of each business€– namely, what cost the business is willing to shoulder for its advertisements. This is rather difficult to determine at first, but once we get some historical data, we can finetune our bids and budget. For our framing shop, we will set a maximum bid price of $1.00 per click. So, we have our account set up, our keywords entered, our ads crafted, and our bids set. We are ready to roll with our sponsored search effort! We activate our account, and typically within minutes, our ads are set to appear. It is really that simple. One could be running a sponsored search campaign in a matter of minutes. However, there are a lot of complex questions, assumptions, and issues underlying this seemingly simple setup. This book addresses those complexities. Potpourri: Sponsored search is a poster child for the concept of technological innovation, which consists of three stages, in a self-reinforcing cycle. The three stages are: (1) a creative and feasible idea, (2) a practical implementation and application, and (3) the diffusion of this technology throughout society [5, p, 27]. It is really quite amazing that in the period of less than one decade, sponsored search grew from conceptualization to a multibillion-dollar enterprise, directly affecting millions of businesses and billions of people. It has shaped the Web as we know it. In addition to its direct impact, it probably has had second-order effects of several billion dollars more [6]. What are these Complex Questions, Assumptions, and Issues? Let’s start with the seemingly simple step of selecting keywords. Which keywords do we select? How many do we select? Why would we select these? The selection of keywords is a critical step in the sponsored search process, and there are literally thousands of guides, checklists, and tools to aid us. However, there are limited documents that address the underlying theories and models to inform us what these guides, checklists, and tools are based on, or why certain keywords work and others do not. In this book, we examine these underlying theoretical aspects. It is a similar case with advertisements. Advertisements in sponsored search systems are typically short, with just a few lines of text (with maybe other elements, such as a small image). Like with keywords, there are numerous checklists and suggestive guides to craft sponsored search advertisements. But why do these suggestions work? Why do certain ads get the potential customer’s attention whereas others do not? What causes potential customers to click on certain ads but not click on others that appear for the same keyword? What about the bidding? It would seem, at first glance, to be a simple process of deciding how much the business would like to spend. In actuality, our bids are part of a complex and intricate online auction process, with multiple competing interests (i.e., ours, our competitor’s, and the search engine’s).

6

Understanding Sponsored Search

These are some of the issues with major components of sponsored search. There are other related components to consider: • Customer Component: How can we determine what the customer is really after? How will the customer behave when shopping online? What causes the customer to make a purchase? • Marketing Component: How does our business engage in the sponsored search process? What are the business’s overall goals and objectives? • Advertising Component: How can we leverage sponsored search to achieve the objectives of our advertising efforts? • Branding Component: What is the image that we want for our business in the online marketplace? Can we leverage sponsored search to increase our brand worth? Conclusion It is for the understanding of these issues that this book is written. No tactics, no checklist, and no implementation advice will address these questions. For this, we must venture into the place of theory and models. Let’s begin. References [1] Wiktionary. 2010. Context. Retrieved January 15, 2011, from http://en.wiktionary.org/wiki/ context. [2] Brin, S. and L. Page . 1998. “The Anatomy of a Large-Scale Hypertextual Web Search Engine.” Computer Networks and ISDN Systems, vol. 30(1), pp. 107–117. [3] Gibson, J. J. 1977. “The Theory of Affordances.” In Perceiving, Acting and Knowing, R. Shaw and J. Bransford, Eds. Hillsdale, NJ: Erlbaum. [4] Jansen, B. J. and Spink, A. 2003. “An Analysis of Web Information Seeking and Use: Documents Retrieved Versus Documents Viewed.” In 4th International Conference on Internet Computing, Las Vegas, NV, pp. 65–69. [5] Toffler, A. 1970. Future Shock. New York: Random House. [6] Johnson, C. H. 2009. Google’s Economic Impact United States 2009. Mountain View, CA: Google.

Word cloud generated by Wordle

2

Modeling the Process of Sponsored Search

This is an opening shot of changing the search engines from white pages to yellow pages. Bill Gross, 1998 as quoted in: Sullivan, D., The Search Engine Report [1].

In our framing shop example of setting up our sponsored-search account, we touched on a process by example without a real appreciation for the underlying complexity of the technology and human interaction inherent in sponsored search. What is the technology that makes the whole process work? What is the business model of sponsored search? Who are the major actors in sponsored search? What are the goals and motivations of these actors? For answers to these and other questions, we examine the sponsored-search model. It is important to develop a generic model of the sponsored-search process. A model is a representation of a complex natural process, simplifying but still embodying the essential attributes. In other words, a model allows us to peel away the unnecessary to get at the critical elements. Adding some flavor to our model, it is worthwhile to begin with a brief introduction of the beginnings of sponsored search, which will shed light on how we got to where we are. Bill Gross [1] was right that the introduction of advertising in the search engine results page was to change everything. Finally, we end this chapter with some of the conceptual jargon of sponsored search. Historical Review of the Early Years of Sponsored Search The first attempt at something like sponsored search was by the search engine OpenText in 1996 [2]. However, the experiment did not go well for a variety of reasons, perhaps the main one being the desire of searchers to not commercialize the searching process. In fact, the company got so many complaints that OpenText removed the feature within a matter of weeks.

9

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Understanding Sponsored Search

Potpourri: To illustrate how early the concept of sponsored search was introduced, the very first occurrence of Web advertising that I could document occurred on October 27, 1994, when Hotwired signed fourteen banner advertisements to display on their site [3, p. 6]. On that day, the Web became a real commercial medium [3]. Supposedly, AT&T was the first company to have their banner ad displayed, although other companies also can lay claim to the fame, including Club Med, MCI, Volvo, and Coor’s Zima. Disclaimer: Other Web-based magazines (a.k.a., Webzines) lay claim to being the first to market with banners ads, including Global Network Navigator, Virtual Journal, Synapse, Medio, and Chaos Control. All, however, were in the 1993 or 1994 timeframe. Regardless, Rick Boyce, Hotwired’s director of business in 1994, is credited with pioneering the idea of banner ads as a major business concept for online companies. Here (supposedly) is something close to what that first banner ad looked like (Figure 2.1).

Have you ever clicked your mouse right HERE?

YOU WILL

Figure 2.1.╇ Image of first banner advertisement.

It reminds me of one of the cheesy roadside billboards that one sees along interstates in the United States promoting those tourist traps just beyond some state line. On February 21, 1998, GoTo.com launched a sponsored-search model in which the search engines ranked “Web sites based on how much the sites are willing to pay to be placed at the top of the search under a real-time competitive bidding process [2].” Advertisements for these Web sites appeared on the search engine results page, and the ad displayed based on the searcher was actively seeking at the time. The conceptualization was relatively straightforward, with a transparent ranking factor (i.e., money), advertisers bidding on exact phrases, and editors checking for relevance. This concept is a first-price auction, where the top bidder gets the top advertising position. GoTo.com also provided nonsponsored listings, provided by Inktomi.com. Potpourri: GoTo.com was the rebranded search engine, World-Wide Web Worm, which was the first Web search engine. Created in September 1993 by Oliver McBryan at the University of Colorado, the World-Wide Web Worm is the grandfather of all Web search engines. It started it all!

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In contrast to OpenText’s experiences, by July 1998, GoTo.com had more than 1,000 advertisers paying between one cent and one dollar a click [4]. This time, there were few outcries against the sponsored-search model. Potpourri: One of the first patents on sponsored search was filed by GoTo.com on May 28, 1998 [5]. Bill Gross is often credited with creating the business model, although other people are also mentioned as deserving credit, including Scott Banister, Vice President of Ideas at IdeaLab at the time, and Jeffrey Brewer, Goto.com CEO at the time. The names listed on the original patent are Darren J. Davis, Matthew Derer, Johann Garcia, Larry Greco, Tod E. Kurt, Thomas Kwong, Jonathan C. Lee, Ka Luk Lee, Preston Pfarner, and Steve Skovran. By 2010, spending on online advertising, primarily sponsored search, exceeded that of spending on print advertising [6]. This is an amazing accomplishment in just twelve years! It parallels and rivals the dramatic rise to prominence of the search engines themselves as gatekeepers to information on the Web. Why was Sponsored Search Successful? It is critically important to understand why sponsored search was successful in 1998, while it was unsuccessful just two years previously. It is said that many technologies are ahead of their time. A more accurate statement may be that successful technologies require the right context. In 1998, the context on the Web was ripe for a change, specifically a new revenue model for Web sites, a new advertising model for businesses, and a new frame of reference for people using the Web. Obviously, much had changed in the two years between the experience of OpenText and that of GoTo.com. As GoTo.com CEO Jeffrey Brewer stated, “Quite frankly, there’s no understanding of how any service provides results. … If consumers are satisfied, they really are not interested in the mechanism [4].” One reason why searchers may have been more accepting of sponsored search is that it combated the nonrelevant manipulation of search results (a nice way of saying spam) that was occurring at the time. Second, banner ads (the main online advertising format at that time) were proving ineffective for advertisers [7]. Banners were becoming commonplace and the novelty was wearing off as clicks dropped from between 10 and 40 percent to about 1 percent in 1997 [3, p. 7]. In 1996, click-through rates were around 7 percent on average, declining to approximately 0.6 percent in 1999 [8]. Seeing this decline in click-through rates, Procter and Gamble (P&G) stunned the industry by announcing they would pay only a $5 cost per thousand rate for banner advertisements [3]. Finally, the concept of click-through rates (CTR) was really coming into its own as an online advertising metric. However, P&G was one of the first companies to insist on paying only CTR for Internet advertising, although it eventually altered its stance by supporting a hybrid impressions-and-clicks model [3]. Specifically, in 1996, P&G

12

Understanding Sponsored Search

made a deal with Yahoo! in which P&G would pay only for click-throughs and not for impressions [9]. The concept of CTR has stuck with the sponsored-search model from its beginning through today, even though many have been critical of its value as metric. According to even early research, CTR has little value as an indicator for return on investment (ROI) optimization because their correlation-to-conversion rates are often low [3]. So, there were a variety of environmental, situational, and commerce factors coming together in mid-1998 that allowed the concept of sponsored search to be accepted by searchers, advertisers, and online businesses. How did Sponsored Search Evolve? Figure 2.2 shows a screenshot of the GoTo.com sponsored-search listings. Note that the bid price is listed as part of the search result. The concept of sponsored search was really quite revolutionary. That a word has a monetary value is truly insightful. Up until that time, search was increasingly viewed as a commodity, even a cost, with search engines basically focusing on developing portals [10]. Sponsored search refocused the search engines back to their core competency of searching and retrieval. Additionally, with advertisers paying only when a potential customer clicked on a sponsored result, it permitted accountability and metrics with online advertising, which was a strategic advantage relative to other forms of solely pushed, impression-based advertising mediums (e.g., television, radio, or print). Again, given that the advertiser did not pay unless a searcher clicked on the sponsored result, the search engine was servicing the ad at no cost until it was clicked on. This laid the foundation for distribution of risk, another aspect of online advertising. The concept of sponsored search really was a game changer for the Web.

Potpourri: When GoTo.com’s sponsored search model was first introduced, many industry analysts were skeptical. Here are some quotes about the process at the time: “It’s kind of strange.”€– Brett Bullington, executive vice president of Excite [2]. “I have questions about whether a consumer cares about this [model] or not.”€– Kate Delhagen, analyst with Forrester Research [2]. “They thought it was tainting the search.”€– Mark Kraatz, manager of corporate Web systems for Open Text (commenting on OpenText’s experience with paid listings [2]). “I’m not sure it’s really providing value to the user, in the long term. I think they want some independent sorting.”€– Rajive Mathur, Lycos search manager [1]. In fact, the whole concept of advertising on the web was questioned. For example: “In the larger picture, advertising is almost irrelevant for the success of the Web.” Jakob Nielsen (1997) Why Advertising Doesn’t Work on the Web. Retrieved March 9, 2011 from http://www.useit.com/alertbox/9709a.html

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Figure 2.2.╇ Search engine results page from GoTo.com.

GoTo.com (renamed Overture in 2001) faced a challenge, however, which was volume of traffic. Namely, they did not have much of it. A key component of the sponsored-search platform is getting enough searchers to come to the site, submit a query, and then possibly click on the advertisements. This has been an enduring aspect of sponsored search advertising platforms€– one has to get a large volume of traffic (i.e., a cost) to the site by offering free searching and then monetize a portion of this traffic with the sponsored-search results (i.e., revenue). This is, of course, a balancing act. A search engine has to monetize the greatest amount of traffic possible, but do it in a way that does not decrease the overall amount of traffic to the search engine. That is, if the searchers that come to the site to conduct free searching are turned off with monetization efforts, they may go away, given that switching costs with searching is near zero. So in a way, each search engine’s sponsored-search platform is both cooperating with its own organic search service and in competition with that same organic search service! It was that way in the beginning and is still the same today. To get traffic, Overture entered into agreements with large Web portals of the time (e.g., CNN, Yahoo!, Microsoft) to serve advertisements on their Web sites (i.e., monetizing their existing traffic). Overture also purchased existing Web search engines, AltaVista and AlltheWeb.com. Potpourri: Yahoo! acquired Overture in 2003 and was later subsumed with Microsoft’s Bing sponsored-search platform in 2010, effectively taking Overture out of the sponsored-search business. Personally, I find it sad. But, the world moves on.

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Understanding Sponsored Search

In 2000, Google launched its first advertising effort, Google AdWords, although the pricing was at first based on number of impressions [11]. However, the program was quite successful, enrolling approximately 350 clients in the first month. Google’s first sponsored-search auction was in February 2002, adopting Overture’s pay-per-click revenue model, but they continued their sales-by-impression model in parallel [12] before finally dropping it altogether in favor of the pay-per-click model. Additionally, Google’s sponsored-search model was introduced with some significant changes relative to the Overture model. First, developers of Google’s AdWords platform changed the pricing scheme from a first-price auction to a more stable second-price auction. In a single-item second-price auction, the highest bidder wins but only pays the second-highest bid price plus some small delta, which is a fancy word for additional amount. (Note: We’ll discuss the significance of this in Chapter 8 where we cover bidding practices.) Second, Google also changed the standard allocation scheme. Instead of ranking advertisements by bid price alone, they computed a quality score derived from the bid amount and the click-through rate. These factors were later enhanced with other factors such as keyword relevancy and landing-page quality. Click-through rate measures the rate at which Web searchers click on an ad’s hyperlink. When combined with Google’s other quality-based criteria, this approach serves to penalize advertisers that use deceptive practices or have poor Web sites. Additionally, it ensures that no advertiser can just buy their way to the top spot while getting no clicks (or it at least makes it more expensive). In other words, Google factored in the concept of relevance to the sponsored-search process, creating a synergy between advertisers and searchers. This introduction of relevance also aided in the acceptance of sponsored search by the Web community. It suggested that search engines cared about providing good search results and not just about the money. It also fit well with Google’s brand image at the time, including point number 6 of its company philosophy, “You can make money without doing evil [13]”. Potpourri: In its most straightforward definition, relevance denotes how well a result on the search engine results page meets the need of the searcher. However, beyond this, the concept of relevance can get very nuanced, very fast. The seminal academic paper on relevance is Relevance: A review of and a framework for the thinking on the notion in information science [14].

Using this approach, Google protected the user’s search experience while also increasing their profits, because users were more likely to click on relevant advertisements. These two auction mechanism changes helped make Google’s auction more stable and more profitable than the original first-price auction.

Modeling the Process of Sponsored Search

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Potpourri: Overture (later known as Yahoo! Search Marketing) updated its pricing scheme to second-price after Google in 2002 and implemented quality-based bidding in the form of its Quality Index in early 2007. So, Google’s sponsored-search model consisted of four synergistic components, improved on over the years, and now characteristic of most sponsored-search models, which are as follows: • Self-service (the advertisers set the price, create the advertisement, monitor the traffic, etc.) • Pay-per-click (the advertiser only pays when searchers click on their ads, instead of paying when the ad is shown) • Auction-based pricing (the set of advertisers in a market vertical determine how much traffic from a given keyword is worth) • Relevance (an advertisement is only shown when triggered by a keyword from the searcher) Google also had one other factor that Overture did not€– search volume! Google had a lot of it. From its founding in 1998, Google had aggressively and solely focused on search and improving search quality. However, search is a costly endeavor and by itself does not make any money. Yet, Google was quite good at search, so they had garnered a large searcher base. The introduction of sponsored search provided a way to monetize this search traffic in a manner consistent with their core search mission. Additionally, the use of click-through rate was consistent with Google’s brand image as a relevant engine. So, unlike the OpenText experience, there was little public outcry against Google commercializing the search process. Yahoo! Search Marketing and Google AdWords remained the dominant players in the sponsored-search area for several years, although some smaller players attempted to and did enter the market at various times. However, the core elements of sponsored search have generally remained unchanged. Potpourri: Why has search traffic gone through such a consolidation? One possible explanation is the Matthew Effect. Based on verses in the Christian Bible, the Matthew Effect basically means that once someone has a lot of something (i.e., like a lot of search traffic), they get more of it. We see the Matthew Effect in a lot of economic concepts, such as the bandwagon effect (i.e., once a lot of people do something, more and more people start doing it). In this brief historical account of the formative years of sponsored search, we have focused on the aspects that lay the groundwork for our foundational understanding. Naturally, there are many aspects, insights, and events not covered here.

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Understanding Sponsored Search

For historical accounts of sponsored search, see [15, 16, 17]. For a nice overview of Google and online commerce, see [18]. For a discussion of the evolution from an economic and communication perspective, see [10]. What has been the Effect of Sponsored Search? The impact of sponsored search can almost not be overstated. It provides the ‘air’ for the rest of the Web ecosystem to function. It services as the circulatory system that brings the “lifeblood” (i.e., cash) to the other components of the Web. It is the “Rainmaker” that carries the other underperforming Web systems. It is the “court square” where the Web community conducts their business. Sponsored search has defined the Web! Sponsored search has played a critical role in supporting access to many free services (i.e., spell checking, currency conversion, flight times, desktop searching applications, etc.) provided by search engines that have rapidly become essential to so many Web users. Without the workable business model of sponsored search, it is doubtful that the major Web search engines could finance anything close to their current infrastructures. These infrastructures provide the capability to crawl billions of Web pages, index several billion documents (e.g., textual, images, videos, news papers, blogs, and audio files), accept millions of Web queries per day, and present billions of links per week, all while servicing most of these queries in a fraction of a second. It is a truly amazing process! Sponsored search has also provided a workable business model for meta-search engines, which is extremely beneficial for searches needing high recall and requiring a thorough coverage of a topic. Sponsored search provides an effective method for overcoming the inherent biases or unintended consequences in the technical implementation of Web search engines by allowing content providers to move their links to the first page of results at a relatively low cost. In doing so, sponsored search has become vital to the success of many businesses. It is fair to say that without sponsored Web search, the Web search engine market€– indeed the Web!€– would look far different than it does today. However, in addition to being a business model for the search engines, sponsored search is a great branding, marketing, and advertising platform for businesses. In fact, the reason sponsored search is such a good business model for the search engines is that it is a good marketing medium for businesses (or any entity) that want to get products in front of people. Let us examine the core process via a model of sponsored search. Conceptual Model of Sponsored Search Sponsored search is continually evolving into an ever-more complex process for satisfying both the desire of potential consumers for relevant information and the need for targeted traffic for advertisers.

Modeling the Process of Sponsored Search

17

Web Content

Advertiser Keywords

Information Need

Keyword Selection

User Query

Cognitive Factors

Traffic Valuation

Ranking Factors

Situational Factors

Infer Searcher Intent

Service Relevant Content

Searcher Intent

1 Advertiser

Goal

Goal

4 Search Engine

Process Content 2 Title Description URL Web page

Interface to Advertiser 5 Review Process Accept Content

Keywords 3

Bid Range Period Payment

9 Web Searcher

Process Tracking

6

Interface to Searcher

Actions

7

Form Query

Accept Query

Submit Query

Keywords and Content Index

Match Query to Keywords

Track Bids Track Displays Track Clicks

Display Links

Bills Provider

Display Result

8 Accept Bid

Review Links Click on Link Review Content

Figure 2.3.╇ The participants, goals, and process of sponsored search on the Web.

Although the payment process and ranking have undergone several incarnations, the other major elements of sponsored search have remained essentially the same throughout its existence [19]. These elements are as follows (see Figure 2.3): 1. Advertiser: an entity (e.g., business, person, or organization) interested in generating user traffic to a particular Web site for some specific purpose and is willing to pay for such traffic. 2. Advertiser Content: a set of keywords (representing concepts) along with the associated uniform resource locators (URLs) pointing to a particular Web site, title, and description contained within an advertisement. 3. Advertiser Bid: offer of payment for specified keywords that are a monetary valuation of traffic to a particular Web site by a provider. 4. Search Engine: an information-searching platform that serves advertiser content on the SERP, relevant Web sites, or e-mail interface in response to searcher queries. 5. Search Engine Review Process: a method utilized by a search engine to ensure that advertiser content is relevant to the targeted keyword on contextual material. 6. Search Engine Keyword and Content Index: a mechanism that matches advertiser’s keywords to searcher’s queries. 7. Search Engine User Interface: an application for displaying advertiser content as links in rank order to a searcher. Typically, the interface displays the sponsored links with nonsponsored links on a SERP, within e-mail, or alongside content on a Web page.

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Understanding Sponsored Search

8. Search Engine Tracking: a means of matching keywords to queries, gathering advertiser content, bidding, metering clicks, and charging providers based on clicks for their displayed links. 9. Searcher: an individual that submits a query and potentially clicks on a sponsored link within a relevant advertisement. Figure 2.3 presents the sponsored-search process as an aspect of information searching rather than strictly an advertising venue. In this framework, the potential customer is performing the role of Web searcher. And this framework is activated with every single search! Think about that for a minute. Think of the traffic on the search engines, with millions and millions of queries. For each one, every time, the sponsored-search process, including the auction for keyphrases, occurs. It is really a phenomenon! As stated by Geddes, “Every search result has three different entities trying to reach their goals. Some times these goals get in each other’s way, leading to poor search results. Other times, they work in conjunction, leading everyone toward success. It is important to examine [the search engine’s goal], the advertiser’s, and the searcher’s goal for each search result” [20, p. 15]. This describes a relationship that is symbiotic, mutually beneficial to all parties involved. In commercial endeavors, we aim for symbiotic marketing that aims to develop mutually beneficial relationship with the customer. Showing relevant content is good for the customer and, consequently, good for the advertiser and for the search engine. In fact, one can show that it can be more profitable for the search engine to not show a nonrelevant advertisement, leaving the ad space unoccupied, than to take the advertiser’s money and show such advertisement [21]. Along the upper half of Figure 2.3, the three major participants (advertisers, search engines, and searchers) have mutually supporting goals. The Web searcher has some need bounded by affective, cognitive, and situational factors, which is what brings the searcher to the search engine and motivates the searcher to submit a query. Advertisers craft terms and search phrases (i.e., keywords) that they believe: 1. are likely to be submitted by searchers; 2. will be applicable to their Web content; 3. will link their content to the underlying intent of the searcher. These advertisers also tailor to the presentation of the ad to conform to demographically targeted searchers, with possibly several presentation variations linked to particular sets of queries within a given advertising effort. Potpourri: The first Google AdWords advertisement was for Live Mail Order Lobsters and was posted less than thirty minutes of the Google AdWords platform going live in 2000 [22]. These listings are known as ads or sponsored results, to differentiate them from the nonsponsored listings, (a.k.a., algorithmic or organic) on the SERP. The search engine can also serve these sponsored results on a vast network of Web sites that are deemed relevant to some searcher action, such as searching on one of these Web sites.

Modeling the Process of Sponsored Search

19

This is not to be confused with contextual advertising, sometimes referred to as content targeting (think: banner ads). The idea of the contextual-advertising approach is that visitors to these Web sites will also be interested in certain ads that are like the content on the Web site. Search engines provide the mechanism for the sponsored-search process to occur, shown in the lower half of Figure 2.3, although the advertiser and the searcher are two major components of this process also. The pay-per-click model is the most common payment method, although others such as pay-for-impression, pay-per-action, and pay-per-call also exist. Advertisers pay the search engine when a user clicks on their link when serviced on the SERP or another Web site. The advertiser can tailor this matching algorithm from exact targeted matches to very loose matches to account for various spellings as well as term usage. The search engine matches the searcher’s query to the keywords that the advertiser bid on. The advertiser pays the search engine via a bid on the keyword. A bid usually includes a maximum price per keyword and can include a period of activation, language, and geographical limitations, among an increasing host of other factors. The bid is the maximum price that the advertiser is willing to pay per click on an ad for a given keyword. For ads serviced on other Web sites, the search engine splits the revenue per click with the Web site owner, although the price advertisers pay per click for these links is typically lower than those on the SERP. Potpourri: Education and training in sponsored search can be difficult, and it is even more difficult to get meaningful practical experience in the area. One endeavor that has done much to address this issue is the Google Online Marketing Challenge. The Google Online Marketing Challenge (or GOMCHA, an acronym first used by Daehee Park, as a student at Penn State) began in 2008 as a worldwide, in-class learning exercise for undergraduate and graduate students in keyword advertising. Working in teams and supervised by a professor, students design, develop, implement, and manage keyword advertising campaigns for small to medium-size enterprises. Lee Hunter, as a Google employee, got the whole GOMCHA program running, with Jamie Murphy, as a professor at the University of Western Australia, serving as the academic lead. GOMCHA is run as both a learning exercise and as a worldwide competition (http://www.google.com/onlinechallenge/). Multiple advertisers may want to pay a search engine for the same term or phrase. In these cases, ranking (i.e., which result goes on top) is handled by an electronic auction that determines the order of the ads. In practice, the highest bidder generally gets the topmost rank; the next highest bidder gets the next rank, and so on. Various search engine sponsored-search platforms also factor in other elements into their

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Understanding Sponsored Search

ranking scheme, such as which sponsored result gets more clicks. This approach helps address the concern that search engines will present less relevant content to the searcher solely for profit and serves to bubble relevant ads to the top of the listing. In practice, the link with the most clicks will generally produce the most profit for the search engine. Therefore, there is a monetary value for all participants in the sponsored-search process to strive for relevant content being presented to a searcher. This is one of the factors that has made sponsored search so successful. The searcher is interested in relevant content, and there is a disincentive for the advertiser or search engine to game the system by showing nonrelevant content. Potpourri: Web search engines employ a variety of techniques to provide results to searchers. These techniques are collectively known as information retrieval, defined as automatically locating unstructured electronic content stored in a computer in response to a query. Typically, the results are ranked to the degree in which they match the query. The classic academic work on information retrieval is Information Retrieval [23]. The point of sponsored search is to provide a mechanism for advertisers to get searchers to visit their Web sites. When a searcher submits a query, reviews the results on the SERP, and clicks on a sponsored link, the searcher’s browser displays the provider’s Web page pointed to by the link. The search engine tracks this click, along with all the other clicks within a given period. At the end of this period, the search engine bills the advertiser, providing various statistics concerning the outcomes of the advertiser’s campaign. From an analysis of these statistics, the advertiser can alter bids, maximum costs per period, and keywords in real time. Advertisers can also change terms or phrases, the price they are willing to bid, the degree of term matching, and even how much they pay in a given time period. By engaging in and “buying” key search phrases, these advertisers become active participants in the information-searching process. Potpourri: Information searching refers to people’s interaction with informationretrieval systems, ranging from adopting a search strategy to judging the relevance of information retrieved [24]. This accounting is one reason that sponsored search is so popular with businesses and organizations. In many forms of advertising, there is little accountability in terms of the cost resulting from impressions (i.e., how many times and when a particular advertisement is shown). Naturally, the searcher is presented with a variety of results, not only sponsored ones. In the first few years of sponsored search, there was some resistance to these advertisements and there will probably always be some resistance. However, in their lab study, Jansen and Resnick [25] reported that searchers with commercial queries are unconcerned whether the results were sponsored or nonsponsored. Their primary

Modeling the Process of Sponsored Search

21

concern is relevance. In fact, when searchers did view and evaluate links in response to given queries, the ratings of the sponsored links were identical to the nonsponsored links. Additionally, Jansen [26] shows that sponsored and nonsponsored links are equivalent in terms of relevance. In sum, sponsored search is a viable revenue model for search engines, a workable advertising medium for businesses, and appears to provide relevant content to Web searchers. The Language of Sponsored Search Our model provides a framework for investigating the foundational underpinnings; however, we must also clearly understand some of the terminology of sponsored search in order to delve deeper into the elements of sponsored search. We introduce these concepts here and then explore them in greater detail in further chapters. Although this review may seem basic to the expert, it is often good to return to the clear and clean process to reground oneself in the area. Let us start with the search engine results page (SERP), shown in Figure 2.4. A SERP is the entire page and all content shown by a search engine in response to a searcher clicking a search or submit button or, if the search engine provides automated searching, by typing in the query. The space on the SERP is known as the screen real estate. To see the entire SERP, a searcher may have to scroll on the browser to the bottom portion of the SERP. Potpourri: Why do search engines list the advertisements in a separate listing? One of the major reasons was a complaint to the Federal Trade Commission (FTC) filed by Commercial Alert in July 2001 against AltaVista, AOL Time Warner, Direct Hit Technologies, iWon, LookSmart, Microsoft, and Lycos [27]. The complaint alleged that the confusion caused in consumers who saw mixed paid and unpaid results in a combined listing constituted fraud in advertising by the search engines. After that, by convention, the sponsored results are listed separately, or at least labeled as sponsored if they are integrated with organic results. The fold is defined as an imaginary horizontal line across the browser that separates the portion of the SERP that the searcher sees when the browser first opens from the part the searcher has to scroll to see. The content on the SERP that the searcher sees without scrolling is referred to as “above the fold.” The content on the SERP that a searcher has to scroll to see is known as “below the fold.” So, the fold is that line that separates the two portions of the SERP based on the act of scrolling or not. Types of search results The shown SERP (see Figure 2.3) has two types of result listings in response to the submitted user’s query. The nonsponsored (or organic) results take up the bulk of the screen real estate. The organic results are composed of result summaries that the

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Understanding Sponsored Search

Figure 2.4.╇ Sample search engine results page showing the location of organic and sponsored listings.

search engine crawls, stores, indexes, and ranks based on its own proprietarily algorithm. Web site owners typically do not pay to appear in this index, and it is these results that usually bring in most of the traffic to the search engine. Potpourri: Getting a result summary for your Web site to appear in the organic results listing is a process known as search engine optimization, as one is optimizing the Web page for a search engine’s ranking algorithm. The other type of search result on the SERP is the advertisement that one typically pays for. The sponsored-search results, as shown, typically appear in three locations. They can appear on the right side of the SERP (known as east, also known as the right rail), above the organic listing (known as north), or below the organic listings (known as south). Potpourri: Web site owners have little control over where their results appear in the organic listing because they have little control over how a search engine indexes Web pages. Search engines can, and do, change their indexing. One of the most infamous major indexing changes occurred with Google just before the busy Christmas shopping season in 2003. Online businesses that had invested significant money and effort in getting their Web sites ranked higher in the organic listings suddenly found themselves out of the top listings.

Modeling the Process of Sponsored Search

23

This indexing change was so infamous, it was dubbed “Florida,” in honor of where it was first noticed. A series of changes to Google’s index, and the resulting search engine optimizations efforts that such changes require, was dubbed the Google Dance. Once Google started updating its index nearly continuously and streamlined the process, the effects were not so dramatic, and phrases like Google Dance were rarely used. Although not shown in Figure 2.4, the sponsored results can also appear intermingled with the organic results; this is known as an integrated-results listing [28]. Potpourri: There have been from time to time position papers and even court cases challenging Google’s ranking of organic results, most notably in the United States. However, these efforts have mostly failed on the basis of the U.S. Constitution’s First Amendment considerations. Although Google (or any search engine) is a technology (i.e., the search engine itself), it is also a legal entity (i.e., the search engine as an incorporated business). As a result, the search engine is afforded (in the United States) certain rights of editorial process (i.e., freedom of speech). Therefore, any legal challenge to the right of a search engine to rank Web pages as it sees fit runs squarely into serious First Amendment considerations [29]. Triggering the sponsored results In Figure 2.4, within the search box are the two terms that the searcher submitted to the search engine. These terms are collectively known as the query. The query length is the number of terms, which can be from zero (happens all the time) up to some limit imposed by the search engine. Along with the click on the search button, the query terms are what trigger the results on the SERP to appear. For the sponsored search results (i.e., the advertisements), either one or both of the terms are linked to a keyword (or keywords) selected by the advertiser, which is then linked to one or more advertisements. So, when a searcher submits a query containing a term that is linked in some way to a keyword selected by an advertiser, the corresponding advertisement appears on the SERP. The linkage between query terms and keywords can come in a variety of flavors, but it generally follows a continuum from precise match to vague match. This level of preciseness is selected by the advertiser. Composition of the advertisement If you notice the advertisements in Figure 2.4, they adhere to a general format, composed of three sections, which is detailed in Figure 2.5. The first section of the advertisement is the headline or title, which is the topmost line of the advertisement. The second section is the snippet or summary, which is the section after the title, typically composed of one or two lines of text. The third

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Understanding Sponsored Search

Figure 2.5. Sample advertisement with highlighted headline, description, and link.

section is the link or URL. This link points to the advertiser’s Web site. The link displayed may or may not be the exact URL of the Web page, but it is typically similar. Collectively, the headline, snippet, and link are known as the ad copy. There may be other components of the advertisement, such as a thumbnail, which is a small image, a geo-location tag, a telephone number, a product review rating, or other metadata. Potpourri: Metadata is data about data. Metadata can aid a searcher by adding value to a chunk of information, especially for multimedia content. Rank placement of the advertisement Note in Figure 2.4 that there are several advertisements on the SERP. Not only are the ads in three different locations (north, east, and south), but the ads are in an ordered listing within each location. The topmost ad in each location is in rank one. The ad below that is rank two, and so on. Ad rank has an effect on several sponsored-search metrics. Key sponsored-search metrics When an ad appears on a SERP, this appearance is known as an impression. We can sum up the number of impressions over a given period to calculate the demand or market (based on searchers’ queries) for our product or service. An advertiser wants an ad to appear on a SERP typically to get the searcher to click on the ad’s link. If our ad appears on the SERP, a searcher can (but not necessarily will) click on the ad. These clicks can be recorded for a given time period. We can sum up the clicks to give us an indication of several aspects of our sponsored-search effort, including the effectiveness of our ad and keyword selection. The ratio of clicks to impressions within the same time period is known as the clickthrough rate (CTR), which is the basis for a host of sponsored-search metrics. The CTR is a key indicator for the health of our sponsored-search effort. We can establish goals for CTR (and other metrics), which are known as Key Performance Indicators (KPIs). An advertiser wants a searcher to click on an ad to get the searcher to the advertiser’s Web page. An advertiser wants the searcher to go to a given Web page to take some action on that Web page, such as to make a purchase, sign up for a newsletter, or download a paper. This action, whatever it is, is known as a convert or conversion. It is really at the heart of our sponsored-search effort, and it is the goal by which all KPIs should be measured.

Modeling the Process of Sponsored Search

25

These are the core terminology of sponsored search and will serve as the basis for our exploration of the area. Potpourri: To illustrate the multiple effects that sponsored search can have on a business, consider the process of choosing a product or brand name today. One approach is to get (or design!) a word that is not currently in use but that implies a word that is in use and conveys a positive image to the potential consumer. Why go through this process? • Search engine technology: Because people use search engines to query the Web, you want a traded term that is not in use for some generic product. In other words, you want it to be unique. • Trademark: If you develop a term that is unique, then you can legally trademark it and begin building your brand. • Cognitive aspect of the user: Although you want a term that is unique, you also want a term that cognitively conveys a brand message to the potential searcher or consumer. • You also do not want any negative implications associated with your term, which your competitors or disgruntled customers can use against you. So, sponsored search touches on an array of physiological, marketing, legal, and technological processes. Foundational Takeaways • We can model sponsored search as a matrix of goals and processes with three actors (i.e., the advertiser, the search engine, and the potential consumer as a searcher). • Each of these actors has unique goals, but these goals are aligned via an economic incentive. • The process of each of the actors work in concert to achieve the individual goal of each (i.e., consumer, search engine, and advertiser). • Given that in sponsored search, the advertiser pays only when a searcher clicks on the advertisements, it is an incentive for the search engine to show only relevant ads. So, the pricing model reinforces the need for only the relevant ads to be shown on SERP. This ensures that both the search engine and advertisers work together to provide a relevant SERP for consumers.

Relating Theory to Practice In our model of sponsored search, we stripped away the nonessential elements to give us a generic model of the sponsored-search process. However, we can take this approach to another level, by adding elements back into the model that reflect the essential elements of a specific domain, search engine, industry vertical, or potential customer (as Web searcher).

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Understanding Sponsored Search

We do this by asking questions, such as: • • • •

What are the particular attributes of the domain? What are the unique characteristics of the search engine advertising platform? What are the specific goals of advertisers in the industry vertical? What are the explicit and implicit goals of potential customers for the domain?

This integrative approach to understanding sponsored search is important, as many specific domains have their own particular attributes that impact the sponsoredsearch process. For example, managing a sponsored-search campaign for a national health care provider is more different than managing a campaign for a local bakery, although the core elements are identical. Conclusion With its rather humble beginnings in 1998, sponsored search rapidly became the primary business model for Web search engines, providing a revenue stream for these gateways to the Web. Running a major Web search engine, with the necessary software, hardware, and people, is a rather costly adventure. Sponsored search provides a monetization of this search traffic, making the search engine economically viable. It is not too much to say that sponsored search has shaped the Web as we know it, financing “free” Web searching that has become indispensable to many of us in our daily lives. As such, especially for those of us that work in the sponsored-search area, it is critical that we understand the process. The presented model of sponsored search strips the process down to its core elements. We see that there are three major components of the sponsored-search system: the searcher (i.e., potential consumer), the search engine (i.e., advertising platform and market maker), and the advertiser (i.e., content provider). These three components have a shared goal of relevant results in response to a query. The potential consumer wants a relevant ad that addresses the underlying need. The search engine wants to service relevant ads to maximize revenue and prevent searchers from switching to other search services. The advertiser wants only viable consumers to click on its ads in order to manage costs. The search engine provides the technology platform for this process to occur. As with any process, sponsored search has developed its own jargon, the immersion in which is necessary to understand the practical implementation. Central to this is an understanding of Web search engines. The SERP is the interface between the advertiser and the searcher. It is generally composed of two types of listings, of which the advertisements can appear in several locations. The ads generally follow a set structure, although the exact format varies with time and search engine. As for metrics, we are interested primarily in the interaction between the searcher and the advertisement. For this, we track various components of this interaction, including the number of times the ad appears, the number of times searchers click on the ad’s link, and the outcome of the searcher visiting the Web site.

Modeling the Process of Sponsored Search

27

However, these metrics tell us what the searchers are doing and not why the searchers are doing what they do. It is the “why” that we explore in the remaining chapters of this book. The first area of exploration is the area of keyword selection. What are these keywords and what is their purpose? Why do some keywords work and others do not? What is the relationship of these keywords to the consumer? An understanding of the underlying theory of keyword selection will help us address these questions. References ╇ [1] Sullivan, D. 1998. “The Search Engine Report.” Vol. 3 (March) ╇ [2] Pelline, J. 1998. “Pay-for-Placement Gets Another Shot.” CNET News, vol. 19 (February). ╇ [3] Kaye, B. K. and Medoff, N. J. 2001. Just a Click Away: Advertising on the Internet. Needham Heights, MA: Allyn and Bacon. ╇ [4] Sullivan, D. 1998. “GoTo Going Strong.” The Search Engine Land Report (July 1). ╇ [5] Davis, D. J., Derer, M., Garcia, J., Grecco, L., Kurt, T. E., Kwong, T., Leee, J. C., Lee, K. L., and Skovran, S. 1999. “System and Method for Influencing a Position on a Search Result List Generated by a Computer Network Search Engine.” Vol. US 6,269361 B1, U. P. Office, Ed. USA, p. 28. ╇ [6] Fontevecchia, A. 2010. Online Ad Spending Exceeds Print, Hitting $25.8 Billion. (December 20). Retrieved January 4, 2011, from http://blogs.forbes.com/afontevecchia/2010/12/20/onlinead-spending-exceeds-print-hitting-25–8-billion-2/ ╇ [7] Johnston, M. 1998. “Web-Design Guru Predicts the Days of the Banner Ad Are Numbered.” CNN.com. ╇ [8] Nielsen/Netratings. 1999. “Click Through Rates.” In The Nielsen/Netratings Reporter (June 17). ╇ [9] Associated Press. 1996. Procter & Gamble World Wide Web ad strategy raises online ire. April 28. [10] Couvering, E. V. 2008. “The History of the Internet Search Engine: Navigational Media and the Traffic Commodity.” In Web Search: Multidisciplinary Perspectives, A. Spink and M. Zimmer, Eds. Berlin: Springer, pp. 177–206. [11] Voge, K. and McCaffrey, C. 2000. Google Launches Self-Service Advertising Program. (October 23). Retrieved January 6, 2011, from http://www.google.com/press/pressrel/pressrelease39.html [12] Krane, D. and McCaffrey, C. 2002. Google Introduces New Pricing For Popular Self-Service Online Advertising Program. (February 20). Retrieved January 6, 2011, from http://www. google.com/press/pressrel/select.html [13] Google. 2010. Google, Corporate Information, Our Philosophy. Retrieved July 13, 2010, from http://www.google.com/corporate/tenthings.html [14] Saracevic, T. 1975. “Relevance: A Review of and a Framework for the Thinking on the Notion in Information Science.” Journal of the American Society of Information Science, vol. 26(6), pp. 321–343. [15] Battelle, J. 2005. The Search: How Google and Its Rivals Rewrote the Rules of Business and Transformed Our Culture. New York: Penguin Group. [16] Fain, D. C. and Pedersen, J. O. 2006. “Sponsored Search: A Brief History.” Bulletin of the American Society for Information Science and Technology, vol. 32(2), pp. 12–13. [17] Jansen, B. J. and Mullen, T. 2008. “Sponsored Search: An Overview of the Concept, History, and Technology.” International Journal of Electronic Business, vol. 6(2), pp. 114–131. [18] Gallaugher, J. M. 2010. “Google: Search, Online Advertising, and Beyond …” In Information Systems: A Manager’s Guide to Harnessing Technology. Irvington, NY: Flat World Knowledge. [19] Jansen, B. 2006. “Paid Search,” IEEE Computer (July), pp. 88–90.

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[20] Geddes, B. 2010. Advanced Google AdWords. New York: Wiley. [21] Libby, B. 2010. Pay Attention to the Man Behind the Curtain. (February 24). Retrieved January 19, 2011, from http://www.thesearchagents.com/2010/02/pay-attention-to-the-man-behindthe-curtain/ [22] Google Inside AdWords. 2005. “An AdWords history lesson.” In Inside AdWords. Mountain View, CA: Google. Retrieved April 4, 2011, from http://adwords.blogspot.com/2005/08/ adwords-history-lesson.html [23] vanRijsbergen, C. J. 1975. Information Retrieval, 2 ed. London: Butterworths. [24] Wilson, T. D. 2000. “Human Information Behavior.” Informing Science, vol. 3(2), pp. 49–55. [25] Jansen, B. J. and Resnick, M. 2006. “An Examination of Searchers’ Perceptions of NonSponsored and Sponsored Links during Ecommerce Web Searching.” Journal of the American Society for Information Science and Technology, vol. 57(14), pp. 1949–1961. [26] Jansen, B. J. and Molina, P. 2006. “The Effectiveness of Web Search Engines for Retrieving Relevant Ecommerce Links.” Information Processing & Management, vol. 42(4), pp. 1075–1098. [27] Ruskin, G. 2001. Commercial Alert Files Complaint against Search Engines for Deceptive Ads. (July 16). Retrieved November 6, 2010, from http://www.commercialalert.org/issues/culture/ search-engines/commercial-alert-files-complaint-against-search-engines-for-deceptive-ads [28] Jansen, B. J. and Spink, A. 2009. “Investigating Customer Click Through Behaviour with Integrated Sponsored and Nonsponsored Results.” International Journal of Internet Marketing and Advertising, vol. 5(1/2), pp. 74–94. [29] Goldman, E. 2010. “Texas AG Investigation.” Retrieved April 4, 2011, from http://blog.ericgoldman.org/archives/2010/09/texas_ag_invest.htm

Word cloud generated by Wordle

3

Understanding Customer Intent for Keyphrase Selection

The Database of Intentions is simply this: The aggregate results of every search ever entered, every result list ever tendered, and every path taken as a result. This information represents, in aggregate form, a place holder for the intentions of humankind€– a massive database of desires, needs, wants, and likes that can be discovered, subpoenaed, archived, tracked, and exploited to all sorts of ends. John Battelle, The Search: How Google and Its Rivals Rewrote the Rules of Business and Transformed Our Culture [1].

When online consumers search for a frame shop, they input a query containing keywords into a search engine. It is these query terms, representing the desires and intentions of the searcher that form the basis of the sponsored-search effort. In setting up sponsored-search campaigns for our framing business, a critical element is selecting appropriate keyphrases. Triggering our ads, these keyphrases are the links between the potential consumers and the products or services that that we want to sell to them. As such, keyphrases are a critical aspect of any sponsoredsearch effort. Our keyphrases link to keywords that compose the searcher’s query. If selection of keyphrases is done poorly, nothing else matters€– not the ads, not the bids, not the metrics, not even the products we are selling. The searcher will not see the ads if the keyphrases do not show the ads. At a strictly mechanical level, the keyphrases that we select must in some way match the terms in the query that the potential customer submits to the search engine. So, referring to our picture-framing shop’s sponsored-search effort, if we had to promote our frames, we could select picture frame as a keyphrase for a given ad within a geographically targeted area near our brick-and-mortar store. When the searcher enters picture frame (or some derivation of this) as a query, the linkage between the query and the ad is made, and our ad appears on the search engine results page (SERP). However, beyond this straightforward mechanical level, there is a much deeper cognitive, situational, and affective linkage that must occur. Namely, the keyphrases must capture accurately what the searcher is looking for (a search for frame could be picture, eyeglass, or house, among many other possible intents), and why the 31

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Understanding Sponsored Search

searcher is looking (is it a cheap frame for a knickknack or a special frame for a gift?). Keywords, as Battelle states [1], contain far deeper meanings, with significant implications for e-commerce, online advertising, and Web marketing. The communication process in which the searcher and the advertiser engage is central to productive keyphrase selection, and the critical element of this process centers on the meaning of information. This information must have an impact on the searcher, and the impact that information can have can be very different for different searchers based on the cognitive, situational, and affective linkages that occur in each individual. • The cognitive aspect is the rational component of information processing during a search. • The situational aspect is the setting in which the search is occurring. • The affective aspect is the emotional component affecting the searcher’s reaction to information. Therefore, the keyphrases we select as advertisers must connect not only to the query (in some mechanical sense), but also link to the searcher’s underlying intent (in some contextual sense). What is causing the person to search in the first place? The keyphrases that make this connection to the searcher’s intent are successful in achieving the goals of our sponsored-search efforts. Making the appropriate connection is the key underpinning of keyword selection and is the reason certain keyphrases work well and others do not. It is primarily this connection that we explore in this chapter. Formally, the context in which this linkage occurs is known as a search market, which is any situation where the buyer and the seller do not immediately find each other. In these situations, and especially for sponsored search, words are important. Potpourri: Words can take on special meaning, well beyond any linguistic aspects, which can really confound keyword advertising efforts. There is probably no better example than the seven words you cannot say on television. The seven dirty words (i.e., filthy words) are seven English words that the American comedian George Carlin used in a 1972 monologue, “Seven Words You Can’t Say on Television.” The seven words became symbolic of both the U.S. government regulation of the national airwaves and efforts to limit lurid content during family television-viewing time, illustrating the impact and varied meaning that these terms can have. http://en.wikipedia.org/wiki/Seven_dirty_words

A quick note on terminology: A keyphrase is a set of one or more keywords that an advertiser selects to trigger an ad. The ad is triggered when a searcher enters a query that matches the keyphrase. A query is a set of one or more terms (a.k.a., keyterms) submitted by a searcher to a search engine. So, we are talking about the same concept, except from different perspectives, as shown Table 3.1.

Understanding the Potential Customers Intent

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Table 3.1.╇ Relationship between searcher’s query terms and advertiser’s keywords Advertiser

Searcher (as a potential customer)

Keyphrase Keyword 1 Keyword 2 Keyword 3 … Keyword n

Query Term 1 Term 2 Term 3 … Term n

Depending on how we structure the matching options, there may be a one-to-one correlation (i.e., the order of the keyword is linked to the order of the query terms). Other times, the order is unimportant. In these cases, a keyword can link to any of the terms in the query. From both the searcher and the advertiser’s perspective, however, we are dealing with words, be it keyphrases or terms. Words are what the searcher and the advertiser use to communicate with each other. To communicate with each other effectively, the searcher and the advertiser must use the same language, which implies each must have a common vocabulary of a sufficient number of words to which each subscribe the same or nearly the same meaning. One way to look at this communication exchange is that the searcher is using a word submitted to the search engine to represent some meaning. The advertiser is trying to derive the meaning behind the word that the searcher submits in order to convince the searcher that their product or service is the solution the searcher is looking for. This exchange of words through the intermediary of the search engine is the basis for communication between the searcher and the advertiser. So, if the searcher enters the term framing, there are several advertisers that might want their ads to appear on the search engine in response to this query. These advertisers could include picture framers, such as our shop, or could include construction companies interested in framing a house, along with many others. At this point, our communication is unclear, as the intent of the searcher is not known. However, with some additional information, such as a second query or a longer query, the searcher’s intent may be more focused. We illustrate this communication process and attempt to infer intent in Figure 3.1. To understand why some keywords are successful and others are not, we must focus on this situation at two levels: the individual level (i.e., the searcher as a potential customer) and the aggregate level (i.e., the market segment of potential consumers for our product). Naturally, the aggregate is composed of a collection of individuals. However, our understanding at the two levels differs greatly. Although we do have some theories to describe the behavior of the individual searcher, these are really little more than heuristics when taken to the practical level, as the multitude of variables intrinsically inherent to the person and extrinsically to the context make hard-and-fast predictions of individual behavior difficult.

34

Understanding Sponsored Search Set of advertisers who wish to display their ad in response to term ‘framing’

User within some contextual situation

Submits a query (e.g., framing)

Search engine processes the query

Fasterframe $50 Off Custom Framing Coupon FASTERFRAME Satisfaction Guarantee www.fasterframe.com

Framing shop #1

Framing shop #2

Custom Frame Mats For Custom Picture Frame Mats Visit Our Experts in Virginia Beach baysidesmouldinginc.adzzoo.com Picture Framing Online 1 (888) 357 3914 Shop Our Huge Variety of Styles, Colors & Sizes. Start Framing Now! pictureandframes.com/framing Building House Browse Photos, And Floorplans For Your Dream Home New Today. www.lennars.com House Framing Contractors Get Free Cost Estimates From House Framing Contractors In Your Area. www.mycontractorlinks.com

Ads display addressing multiple intents

Construction company #1

Construction company #2

Other seemingly random advertiser

Figure 3.1.╇ Example of query and the ads in response with unsure intent in the linkage between keyterms and keywords.

However, predicting behaviors at the aggregate level is more certain. With enough historical data from enough individuals, we can do much more than describe behavior with heuristics. At the aggregate level, we can make some inferences and predictions of behaviors. However, an understanding of the individual is important, critically so. We begin by examining the theoretical foundations of information processing at the individual level, relating this to the function of keyword selection in sponsored search. We then move to the aggregate level.

Human Information Behavior at the Individual Level A fundamental flaw with many sponsored-search efforts€– perhaps a holdover from mass media advertising€ – is that the advertiser views their potential customers or market segment in a mass (i.e., a collective, a group). This viewpoint leads to a blurred focus in keyphrase selection. Instead, it is essential for effective keyphrase development to connect to the individual that wants to buy what the business wants to sell. Picture all the dimensional aspects that compose a typical man or woman who is likely to buy your product. Target your keyphrases for this person. Chances are that there is another typical type of man or woman that is likely to buy your product and select other keyphrases. Target another set of your keyphrases for this person. There could be many other such individuals.

Understanding the Potential Customers Intent

35

So, this visualization process of the individual involves developing several personas of the typical customer. At the individual level, we make the assumption that the individual is in some state of information acquisition, either actively or passively gathering information. This assumption is based on the theoretical premise that having more information is more advantageous than not having information. Based on this premise, people whose behavior is guided or controlled by information are more likely to succeed than those people whose behaviors are not guided [2]. This concept is adhered to in several academic fields, including information science [3], finance [4], and natural sciences [5]. Some researchers have even argued that access to information is a vital human function [6], and increased information can contribute to fairness and less bias in decisions [7]. Potpourri: Although most researchers generally adhere to the notion that some information is of benefit, there is a wide range of research that suggests some people actively seek to avoid information (i.e., business owners who may not want to know the true state of their business or terminally ill patients who do not want to know their true condition), or that too much information actually decreases the effectiveness of decision making. Of course, anyone who has managed a project of any complexity will also tell you that at some point the cost of gathering information begins to exceed the benefit of that information. So, our theoretical assumption is more of a guideline than a hard-and-fast rule. Our assumption is that information is good and that the searcher wants at least a certain amount of it. But how do people go about gathering information? People acquire information about the external world by exteroceptors (i.e., a sense organ or a receptor organ that responds to external stimuli), namely vision, audition, olfaction, tactile, and taste. In everyday terms, these are the five senses: eyes, ears, nose, hands (as a representative of touch), and mouths. Sometimes, we are actively seeking information. Other times, we are passively receiving information, and yet other times, we are actively seeking one type of information but receiving another type. Regardless, the brain is continually sifting this stream of information for relevant clues or signals and filtering out the irrelevant signals (i.e., noise). Depending on the circumstances, today’s noise may be tomorrow’s relevant signal. Human information processing is how people receive, store, integrate, retrieve, and use the information gathered by their senses, with a focus on the cognitive aspects of information use [8]. In sponsored search, we are concerned with words. Long ago, people recognized individual words (in natural languages like English; not true in all languages) by the way they sounded [9]. Later, rules of grammar, spelling, and syntax were devised to permit words to be written, and thus we have the text and written text. Therefore, rather than recognizing a word by sound, one could recognize a word by the way it looked. A

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Understanding Sponsored Search

person could then receive information via the visual instead of auditory input, although one can say that we still “hear” the word in our minds even when it is written. For sponsored search, we are primarily interested in this visual input, in that we want the potential customer to see our ads. These ads appear due to the searcher entering a query into the search engine. So, instead of saying a word, the searcher types it into a search engine or speaks and a machine translates the word into text. As such, we are more interested in the actual behaviors of the searchers, especially in their development of the query and the terms they select for the query. This is not to say the cognitive processes are not important (they certainly are) but by necessity we focus on the effect that these cognitive processes have on actual behavior. For keyword selection, we are interested in the query that the searcher formulates. Where does the searcher get these query terms? The answer to this question illuminates the keyword-selection process. In the broadest sense, query terms can come from internal or external sources. However, formulating the query is grounded in human information behavior and processing. • Human information behavior is the totality of human behavior in relation to sources and channels of information, including both active and passive information seeking and information use [10]. • Human information processing is the method of acquiring, interpreting, manipulating, storing, retrieving, and classifying recorded information [11, 10]. There are a number of personal factors that influence information processing in an individual, including economic class, culture, education, knowledge, and gender [12]. Human information behavior is linked to human information processing, in a feedback cycle (i.e., information behavior → information processing → follow-up behavior). So, whereas human information behavior is concerned with external and exhibited behaviors of the searcher, human information processing is concerned with the internal aspect of the searcher as they assimilate information. Figure 3.2 illustrates the process. The final aspect of human information behavior is information use behavior, which consists of the physical and mental acts involved in incorporating the information found in the searcher’s existing knowledge base. Therefore, it may involve physical acts such as annotating sections on a Web page to note their importance or significance, as well as mental acts that involve, for example, comparison of new information with existing knowledge [10]. Placing this Behavior → Processing → Use sequence (see Figure 3.2) within the context of sponsored search, there is a searcher that desires information and, via the query, is taking the first step in a communication process. The advertiser, via the ads linked to these keyterms by keywords, is communicating with the searcher by providing information. The searcher may read the ad, click on the ad, and read the content on the landing page. The searcher then processes in some manner this new information. The searcher decides what to do with this information and whether or not they intend to use it. With each of these steps, there is cognitive activity. Sometimes this cognitive activity occurs immediately. Other times, cognitive activity occurs (or continues)

Understanding the Potential Customers Intent Human Information Behavior

Human Information Use

Human Information Processing

Feedback Loop

37

Feedback Loop

Figure 3.2.╇ The human information behavior€– processing€– use sequence.

after the communication has been completed, as the searcher reflects further on the information received and integrates it with existing information, beliefs, thoughts, concerns, feelings, and so on. This helps explain the common phenomenon that occurs in sponsored search, where the searcher may view what appears to be a very relevant ad and do nothing. The searcher may perhaps return to the same ad several times before eventually making a purchase. It is all part of information-processing behavior. The potential customer as searcher Human information behavior can be subdivided into more focused sets of behavior, as shown in Figure 3.3. From Figure 3.3, human information behavior is the broadest area, addressing all aspects of human information interactions. A subset of this is information-seeking behavior, which encompasses the range of information seeking employed in discovering and accessing information resources (both humans and systems) in response to goals and intentions. Information-searching behavior is a subset of information seeking, referring to the actions involved in interacting with an information search system [13]. Information searching is the manifestation where human information behavior and sponsored search meet. At the highest level, humans access various information objects, and diverse information systems support human information behavior. At the middle level, humans seek information and eventually use the information gained from information-seeking systems. Either human resources or information from other resources provide affordances to support particular human informationseeking behavior. At the micro level, primary actions taken by humans during the process of interacting with information-retrieval systems are searching and browsing [13]. It is this subset of information searching that we are most interested in for sponsored search. Information searching refers to people’s interaction with information-retrieval systems, ranging from adopting a search strategy to judging the relevance of information retrieved [10]. The information part of information searching is an overloaded term, as the searcher may be looking for something other than information. For this book, we are specifically examining Web searching, which simply is information searching on the Web.

38

Understanding Sponsored Search Nested Framework of Human Information Behavior Human Information Behavior, Interacting with various forms of information through all channels for both active and passive information seeking and use Human Information Behavior is the collection of behaviors people engage in during the process of information acquisition.

Information Seeking Behavior, seeking for information in response to goals and intentions by interacting with systems and humans Information Seeking Behavior can involve interactions with a variety of information sources, from technology to the people to books to objects.

Information Searching Behavior, actions involved in interacting with information search systems For sponsored search, information search behaviors are the interactions that we are primarily interested in. Human Information behaviors are the conduits for human information processing, which is the methods of making sense of the information that we gather.

Figure 3.3.╇ Framework of human information behavior, information-seeking behavior, and �information-searching behavior.

Potpourri: Interestingly, the first academic studies of Web information searching using query logs from search engines (Excite, Infoseek, and AltaVista) all came out within a few months of each other (late 1998 and early 1999) and in the same outlet (SIGIR Forum). The three journal articles are: Jansen, B.J., Spink, A., Bateman, J., & Saracevic, T. (1998). Real life information retrieval: A study of user queries on the Web. SIGIR Forum, 32(1), 5–17. Kirsch, S. (1998). Infoseek’s experiences searching the Internet. SIGIR Forum, 32(2), 3–7. Silverstein, C., Henzinger, M., Marais, H., & Moricz, M. (1999). Analysis of a very large Web search engine query log. SIGIR Forum, 33(1), 6–12. In mechanical concepts, the term search denotes the specific behaviors of people engaged in locating information [14, p. 5]. In sponsored search, we focus on the economic perspective of search theory, which is the study of an individual’s best strategy when choosing from a series of potential opportunities of varying quality. Within the confines of sponsored search, these opportunities are the ad, as surrogates for the products or services we are trying to sell. In search theory, we are primarily interested in whether or not the searcher searches again, thereby delaying the purchase decision and incurring some delay cost, or stops searching, coming to a decision on whether or not to buy. From search theory, we can

Understanding the Potential Customers Intent

39

develop search models for various contexts illustrating the balancing of the cost of delay against the value of searching again. Associating keyphrases and queries When engaging in information searching, the searcher is utilizing the search engine to locate some type of content. For now, we consider content to be anything accessible via a search engine. We consider this content to be multimedia, composed of one or more media types, such as text, images, video, or audio content. Fundamental to sponsored search is the linkage between the keyphrase that the advertisers bid for and the keyterms that the searchers use in their queries. For both the advertiser and the searcher, these keyphrases and terms represent the underlying product, service, or offerings from the advertiser that the searcher, as a potential customer, is looking for. This integration of search and advertising is a salient attribute of the sponsoredsearch business model [15] and is the critical linking for keyword selection. Figure 3.4 illustrates this linkage between keyphrases and keyterms. Establishing the links among searcher need, query terms, and advertiser keyphrase: Search, experience, and credence products and services Focusing first on searcher needs, we are faced with the question, “how can we classify needs?” For sponsored search, we make the assumption that the searcher is looking for a product or service, including information about the product or service. Nelson [16] classifies products (we include the concept of services) into three general types: search, experience, and credence (SEC) goods. This product classification is especially useful, as it captures the underlying uncertainty that consumers face in purchasing these products, and why the consumer is communicating via the search engine to get additional information. According to the SEC framework, attributes of goods can be analyzed in terms of three properties: search, experience, and credence [16]. “These properties are used to categorize the point in the purchase process when, if ever, consumers can accurately assess whether a good possesses the level of an attribute claimed in advertising” [17, p. 433]. • Search goods have attributes that are identifiable through inspection and are accessible to the consumer prior to purchase (e.g., music downloads, pay-for-view movies, books, clothes, etc.) • Experience goods have attributes that are revealed only through consumption by the consumer (e.g., brokerage service, vacation packages, and healthcare) • Credence goods have attributes where the consumer can never be certain of the long-term quality and/or value, even from observations and use (e.g., psychics, tax services, medical treatment, and counseling services) Now, certainly, the boundaries between these categories can be fuzzy. It is best to consider these classifications to represent regions in a continuum, with significant overlap, as shown in Figure 3.5.

40

Understanding Sponsored Search

Searcher Need (Content: A user that is motivated with a desire to address a need by searching on a Web search engine.)

Query (Content: A set of one or more terms that the searcher believes is an expression of the underlying need they are trying to address.)

Translates the Need into a Set of Terms

tes

ocia

Cognitively Linked

Cognitively Linked

Ass

Matching Criteria (Content: One of a set of possible matching criteria linking the terms in a searcher query to the advertiser keyphrase.) Ass

ocia

Advertisement (Content: A sponsored search result that the advertiser believes will be perceived by the searcher as directing them to a website that will address their need.)

tes

Keyphrase (Content: A set of one or more keywords that the advertiser believes that the searcher will enter when trying to address a need fulfilled by a product or service the advertiser is attempting to sell.)

Triggers

Figure 3.4.╇ Relationship of the searcher, query, keyphrase, and advertisement. Spectrum ...

... of Search Goods Search goods are products or services for which the consumer can determine all product attributes pre-purchase. Spectrum of Experience Goods Experience goods are products or services where the consumer must actually use the products to know the attributes.

Spectrum of Credence Goods Credence goods are products or services where the consumer may not know the attributes even post-purchase.

Figure 3.5.╇ Spectrum of SEC goods illustrating an overlap among classifications.

The important factor to consider for sponsored-search efforts is that the defining characteristic underlying this segmentation of goods, namely the prepurchase quality uncertainty of the product/service to the searcher, increases from search to experience to credence goods as quality becomes more difficult to judge [15, 18]. This level of uncertainty has a significant impact on the keyphrase and query term selection by advertiser and searcher, respectively. Thus, the searcher’s underlying motivation for information searching is uncertainty reduction. When a searcher is lacking in knowledge of a product, service, or the expected outcome of consumption, the searcher is more likely to engage in uncertainty-reduction processes to minimize the risk and to maximize the consumption value [19]. Naturally, this process of uncertainty reduction is moderated by cost (i.e., if the product or service is inexpensive, the consumer may just purchase it rather than expend the time and effort searching).

Understanding the Potential Customers Intent

41

Table 3.2.╇ SEC goods with impact on advertiser and searcher Type of product or service

Impact of query selection (searcher)

Effect on keyphrase selection (advertiser)

Search

Searching for specific product or service attributes Searching for locations to see, touch, smell, etc. the product or service Searching for reviews, blogs, commentary on product or service

Select keyphrases in line with product attributes Select keyphrases to guide searcher to off-line store

Experience

Credence

Select keyphrases to guide searcher to social media aligning with marketing goals

We also have to be careful here, as there may be several motivations for searching along with reducing uncertainty, including entertainment or risk reduction. Sponsored-search efforts have to address this range of motivations. However, uncertainty reduction is undoubtedly a major component of e-commerce searching, and the SEC goods framework can help explain significant portions of the consumer searching behavior, as shown in Table 3.2. The SEC goods provide a framework that explains much consumer searching. For example, I have a friend who owns a high-end calendar business, with exquisite photos for niche markets, such as kittens, airplanes, and fishing. Most of these customers are repeat customers, many of whom bought a calendar of his at some big-box reseller. Why the majority of repeat business? High-end calendars are primarily an experience product. Customers want to see the pictures and feel the quality of the paper. So, my friend advertises in his sponsored-search campaigns mainly on branded terms (name, URL) to jump ahead of the big-box calendar sellers because he makes more money selling directly. However, he participates with the in-store resellers to provide the experience to his potentially future direct customers. So, from this SEC framework, advertisers can focus on search terms that best fit their product. This is still a difficult task, as years of empirical research has shown that the length of queries is typically very short [20] or very long, which is likely the result of searcher’s cut-and-pasting in selections of text. The reason for this stability of query length during a period when technology has rapidly increased is that the cognitive aspects of the searcher have not changed. In other words, the ability of technology to provide information has increased exponentially (i.e., Moore’s Law), but the ability of humans to process it has remained stable.

Potpourri: Why are most query terms short? Some of it may have to do with simple information needs. It may have to do with the cognitive limits of our memory (i.e., the human processing and storage power). (Continued)

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Understanding Sponsored Search

Based on Claude Shannon and Norbert Weiner’s information theory research [21], Harvard psychologist George A. Miller [22] proposed the theoretical construct, known as the Magical Number Seven, Plus or Minus Two. The gist of the construct is that the typical human can process about seven chunks of similar information at any instant in time (sometimes a couple more, sometimes a couple fewer). The concept of chunking is now a foundational element in many theories of memory. Miller’s work included the concept of chunking information in larger and larger groupings while still keeping the concept of seven chucks of similar types. The impact of this construct on sponsored search is that it helps explain the shortness of queries. Words in ads probably need to be presented in chunks that the searcher can remember or recognize, and that the searcher has a limit to the amount of information he is able to use at any given time. What do we know about the actions of the individual searcher? Considering this conceptualization of Web search for consumer products or services during information searching in a period of uncertainty reduction, what can we say about the searcher’s specific behaviors? A body of empirical work supports the theoretical constructs of the principle of least effort, the uncertainty principle, and information obtainability. Principle of least effort.╇ The principle of least effort states that when solving problems, a person tends “to minimize the probable average rate of his or her work-expenditure (over time), meaning use the least amount of effort” [23, p. 1]. This proposition that an organism generally seeks a method involving the minimum expenditure of energy in striving for a goal is one of the most enduring tenets in Web searching. The principle of least effort is related to the psychology principle of satisficing [24]. Satisficing takes the view that people have evolved to make decisions quickly. In order to make these quicker decisions, people choose from a subset of options instead of considering all possible options before acting. By applying some general rules, statistically, the best option in that subset should be close to the best option in the whole set of options, which has been borne out in empirical research on Web search. We see similar rational in the concept of framing [25], which has implications for sponsored search [26]. The principle of least effort is embedded in theories such as information foraging [27] as well. With the information-foraging paradigm, humans forage for information looking for answers according to this searching theory, just like animals foraging for food with time and energy constraints. Given the abundance of information and the increasing growth rate of new information on the Web, information foraging states that humans adopt adaptive strategies to optimize their intake of useful information per unit cost. The information-foraging theory illustrates the application of the principle of least effort as people take actions that get the information they want or think they need with the expenditure of the least cost.

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We also see the application of the principle of least effort in sponsored search in the searching attributes of potential customers. Queries are extremely short [28]. There is limited viewing of results or result pages [29, 30]. There is limited viewing of results below the fold [31]. Session duration is very limited [32]. Time on a Web site is restricted [29]. All of these behaviors point to the same thing: Searchers will expend the least amount of effort possible to get satisfactory results. The uncertainty principle.╇ The uncertainty principle [33] states that the earlier stages of information searching are initiated by a lack of understanding or a limited knowledge, and this cognitive state is uncertainty. The affective symptoms of uncertainty are associated with being vague and unclear about a search topic. The level of uncertainty is connected to information desired and search tactics [34]. Certainly, this makes intuitive sense, but it is important to be clear about what is the motivation for a person to search. A focus on the uncertainty helps in this regard. Generally, uncertainty deals with a state of limited knowledge by a user in a given context. This uncertainty may be how to express a need, what that need means, or the changing of previously held beliefs. As the information search progresses, the searcher develops a clearer focus of the topic and a shift occurs from feelings of uncertainty, confusion, and frustration to feelings of increased confidence. The uncertainty principle is closely related to sense-making’s concept of a gap or discontinuity [35] that the individual conceptualizes in a certain situation. This situation does not permit the individual to move forward without obtaining new knowledge and constructing a changed sense. Based on new information obtained, the individual can move to bridge the gap and proceed after crossing the gap. The uncertainty principle is also inherent in the Anomalous States of Knowledge (ASK) model [36] of information seeking. In sponsored search, as with most concepts of consumer search, there is an assumption of the reduction of uncertainty concerning a product choice. Information obtainability.╇ A construct that has clear impact on sponsored search is the notion of information obtainability. That is, the more accessible the information, the more likely it is that people will use that information. Stated explicitly, “The more difficult and time consuming it is for a customer to use an information system, the less likely it is that he [sic] will use that information system” [37, p. 46]. Phrased more succinctly, information will be used in direct proportion to how easy it is to obtain [38]. In fact, the entire concept of Web search has been concerned with making it easier for the searcher to access online information. What do we know about the intent of the individual searcher? In addition to the theoretical constructs of the principle of least effort, the uncertainty principle, and information obtainability, we can also determine with increased accuracy the topic (i.e., what is the subject of the searcher’s query) and the intent (i.e., what type of content the person is searching for). The topic of a term is related to the use of the word, an inherent aspect of language and communication. Like most words in the English language, key phrases can be

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Understanding Sponsored Search

categorized as nouns, verbs, adverbs, adjectives, prepositions, or pronouns. Research has shown that most, although not all, queries are composed of primarily nouns [39] on stop words (a.k.a., skip words). The user intent [40, 41, 42] is somewhat unique to Web searching. So, given the importance and application of intent, we cover it here. What can we learn from the underlying intent of a searcher’s key terms? Naturally, different queries often have different underlying needs, and these underlying needs often induce different types of searcher behavior, from click-through behavior to browsing behavior. For example, empirical studies have noted that broad informational queries (e.g., digital camera) require more browsing by searchers relative to more focused queries (e.g., find a Nokia camera) [43]. The research into user intent in Web search begins with Broder [40], who proposed three broad user-intent classifications for Web queries: navigational, informational, and transactional. This framework was based on empirical observation, and it has been supported by a string of empirical research in the area of Web searching. For example, Spink and Jansen [44] report that e-commerce-related queries varied from approximately 12 percent to 24 percent using various Web search engine transaction logs. Jansen, Spink, and Pedersen [45] stated that there was a significant use of search engines as a navigation appliance. The researchers report that the top fifteen queries from a 2002 AltaVista search log (e.g., google, yahoo, ebay, yahoo.com, hotmail, hotmail.com, thumbzilla, www.yahoo.com, babelfish, mapquest, nfl.com, nfl, weather, www.hotmail.com, and google.com) were all likely expressions of a navigational intent. It is apparent that the hypermedia environment of the Web provides a unique capability of using search as a specialized form of browsing. Expanding on Broder’s classifications, Rose and Levinson [42] classified search queries using the categories of informational, navigational, and resource, with hierarchical subcategories of each. What is user intent? User intent is the resource specified by the affective, cognitive, or situational goal expressed in an interaction with a Web search engine. Referring to Belkin’s states of a searching episode [46], intent is akin to goal, and expression akin to method of interaction. Unlike goal, however, intent is concerned with how the goal is expressed because the expression determines what type of resource the user desires to address his or her overall goal. Pirolli [27, p. 65] makes a similar delineation between task (i.e., something external) and need (i.e., the concept that drives the information-foraging behavior). Saracevic’s stratified model [47, 48] proposes that user expressions to an information-searching system are based on affective, cognitive, or situational strata. Certainly, the query is a key component of this expression of intent. The importance of the query is obvious by the considerable amount of research examining various aspects of query formulation, reformulation, and processing [49, 50, 51, 52]. Pirolli [27, p. 65] refers to the query also as an external representation of the need. Note that the query is often an inexact representation of the underlying intent [53, 54, 55, 56]. Derived from research [40, 42], user intent within each category is defined as one of the following:

Understanding the Potential Customers Intent

45

• Informational searching: The intent of informational searching is to locate content concerning a particular topic to address an information need of the searcher. The content can be in a variety of forms, including data, text, documents, and multimedia. The need can be along a spectrum from very precise to very vague. • Navigational searching: The intent of navigational searching is to find a particular Web location. The Web location can be that of a person or organization. It can be a particular Web page, site, or hub site. The searcher may have a particular Web site in mind, or the searcher may just “think” a particular Web site exists. • Transactional searching: The intent of transactional searching is to locate a Web site with the goal of obtaining some other product or service on that Web site. Examples include purchasing a product, executing an online application, or downloading multimedia. In less academic language, we can define the intent of these three broad categories as: • Informational€– finding • Navigational€– traversing • Transactional€– getting Each of these three major categories can be further subdivided [41]. Table 3.3 presents a three-level hierarchical taxonomy, with the topmost level being Informational, Navigational, and Transactional. Each of these level-one categories has several level-two classifications. Some classifications also can involve a third-level classification. Table 3.3 also presents definitions of each of the classifications in the user-intent taxonomy. Graphically, Figure 3.6 presents a hierarchal overview of the user-intent taxonomy, along with potential impact on sponsored search efforts. With these concepts of human information processing, constructs of individual searching behavior, and advances in determining the intent of the searcher, we can project these behaviors from the individual to the aggregate level. Human Information Behavior at the Aggregate Level We now know some things about the individual searcher. Conceptually, we market toward the individual [57]. However, by necessity, we must deal with market segments, which is a subset of the total market of potential customers. This market segment of potential customers is an aggregate set of potential consumers (typically people, but can also be other businesses) who possess similar sets of attributes resulting in the wanting of similar products and/or services. Using market segmentation, the advertiser can describe and perhaps predict what the potential consumer will do. This ability to predict can help in determining what keyphrases should be selected for sponsored-search effects. This segmentation is concerned with human information behavior at the aggregate level.

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Understanding Sponsored Search

Table 3.3.╇ Definitions of classifications of Web queries Levels Level One (I) Informational: queries meant to obtain data or information in order to address an information need, desire, or curiosity. (N) Navigational: queries looking for a specific URL. (T) Transactional: queries looking for resources that require another step to be useful.

Examples of queries Child labor law

Capital one Buy table clocks

Level Two (I, D) Directed: specific question (I, U) Undirected: tell me everything about a topic (I, L) List: list of candidates (I, F) Find: locate where some real world service or product can be obtained (I, A) Advice: advice, ideas, suggestions, instructions (N, T) Navigation to transactional: the URL the user wants is a transactional site (N, I ) Navigation to informational: the URL the user wants is an informational site (T, O) Obtain: obtain a specific resource or object (T, D) Download: find a file to download (T, R) Results Page: obtain a resource that one can print, save, or read from the search engine results page

(T, I) Interact: interact with program/resource on another Web site

Registering domain name Singers in the 1980s Things to do in Hollywood ca PVC suit for overweight men What to serve with roast pork tenderloin Match.com Yahoo.com Music lyrics Mp3 downloads (The user enters a query with the expectation that ‘answer’ will be on the search engine results page and not require browsing to another Web site.) Buy table clock

Level Three (I, D, C) Closed: deals with one topic; question with one, unambiguous answer (I, D, O) Open: deals with two or more topics (T, O, O) Online: the resource will be obtained online (T, O, F) Off-line: the resource will be obtained off-line and may require additional actions by the user (T, D, F) Free: the downloadable file is free (T, D, N) Not Free: the downloadable file is not necessarily free (T, R, L) Links: the resources appears in the title, summary, or URL of one or more of the results on the search engine results page

(T, R, O) Other: the resources does not appear one of the results but somewhere else on the search engine results page

Nine supreme court justices The excretory system of arachnids airline seat map full metal alchemist wallpapers Free online games “Family Guy” episode download (As an example, a user enters the title of a conference paper to locate the page numbers, which usually appear in one or more of the results.) (As an example, a user enters a query term to check for spelling with no interest in the results listing. I do that!)

Understanding the Potential Customers Intent

Informational

Directed

Closed

Undirected

Open

List Find Advice

Navigational

to Informational

Obtain

Offline

Download

Free Cost

Results Page Interact

Sponsored Search Impact Primarily searchers who are conducting research on which products might address their need and transitioning to comparison shopping Searchers who know where they want to gho; opportunities for branding

to Transactional

Online

Transactional

47

Links Other

Searchers who have completed most of their research and are now looking to buy or abtain. Those looking for ‘free’ may need to be filtered out. The SERP is good place to provide other contact information.

Figure 3.6.╇ Hierarchy of user-intent classification with impact on sponsored search.

To investigate aggregate information behavior, let us once again begin with the concept of search, but instead of search as a set of individual actions, let us consider search as an economic concept. When we do this, we find that, unlike at the individual level where we had little more than guidelines, we can not only develop rules at the aggregate level but also make some fairly accurate predictions on this information behavior. Potpourri: In his seminal science fiction series, The Foundation Trilogy, Isaac Asimov introduced the concept of psychohistory, an inferential scientific discipline based on the premise that, with enough data, one could predict what a set of people would do, even if one could not predict what an individual person would do. For many years, this was just science fiction. Not any longer. The massive amount of data collectable on the Web is providing insights into advertising, customer behavior, language translation, financial markets, disease outbreaks, election outcomes, and many other situations. So, Asimov might have been on to something. The data is just now catching up. Let us briefly discuss consumer searching; we will address consumer searching in more detail in Chapter 5. However, we need some background on it to make sense of our discussion on keyterm selection. We anchor our discussion in that of consumer search research [58].

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Understanding Sponsored Search

One can theoretically model consumer search as a process where the searcher is in a state of deciding to seek out additional information (i.e., searching again) or not seek additional information (i.e., stop searching). This decision process is a function of the expected benefit of any additional information [59], with the benefit of searching being a reduction in uncertainty. As the searcher gathers additional information from additional searches, the searcher’s expected benefit of seeking new information decreases (i.e., their uncertainty is reduced), and this increased confidence results in a lower probability of the searcher soliciting new information (i.e., doing an additional search). Now, one can model this consumer search process by developing a model of the search process as the probability that individual i searches an xth time (i.e., submits an addition query xth) as a decrement of the probability of visiting the (xi –1)st site [based on the work of 17, 36]: Pr[ Xi = xi ] =

( xi − 1)θi Pr[ Xi = xi − 1], xi = 2, 3, ..., xi

Equation 3.1.╇ Probability model of consumer search.

The model presented in Equation 3.1 is simply a rephrasing of the search behavior described earlier, except it is now presented in mathematical symbols rather than words. The model is recursive. Any series of states in the searching process is just composed of a set of individual search states. Therefore, we can present this recursive model as a logarithmic distribution. The revised model is presented in Equation 3.2, where ai = –[ln(1–θi)]–1 and 0 : : : > Ø k, where Øi is the probability that the user clicks on the advertisement in slot I (i.e., the CTR of 1 > i). r
Assume that higher slots get the best CTR and that CTR will generally fall geometrically. That is, CTR decreases by position and follows some algorithm sequence. r
A set of n advertisers participating in the auction, each with a private valuation vi for a click, v1 > : : : > vn (i.e., a set of advertisers who each set their own bid on a click for an ad-keyphrase combination). r
Assume that k > n (i.e., there are always more ad slots than advertisers). r
With knowledge of the mechanism and of their own private valuations, each advertiser submits a bid to the auction. We denote player i’s bid by bi. r
The mechanism: r
computes an allocation χ of the k slots to k different players; r
χs is the identity of the player that is allocated to slot s (i.e., the search engine assigns some ad slot to some advertiser’s ad); r
charges a price ps to the player χs for each click on his advertisement with ps b2 will suffice to obtain the highest position. > b2 for i = 1,  θ  bi = υi − i (υi − bi + 1) for 2 ≤ i ≤ k, θi − 1  for k < i ≤ n. υi Equation 8.3.╇ Effect of quality score on advertiser bid.

This is Nash equilibrium of the GSP for which there is no incentive for any advertiser to dramatically change their bidding strategy.

Foundational Takeaways • Sponsored-search auctions are online auctions where the bidder pays a small delta more than the second-highest bid. • There are three players in the auction that you need to be aware of: you as advertiser, the other advertisers, and the search engine. • In general, although there are incentives for each bidder in the GSP auction to bid the actual value of the keyphrase, this is not true in all scenarios. The GSP is not a pure truthful auction in the sense that advertisers can, and occasionally do, enter bids that do not represent their true value. • As auction and market maker, there is incentive in the auction for the search engine to maximize revenue and to drive the auction to stability by offering a worthwhile searching experience to the searcher. • Although the auction is for keyphrases, the ultimate item of value is the ad position on the SERP, which is correlated to customer traffic. • The bid price for the keyphrase does not directly determine the ad position, but the general principles of the GSP auction still hold. • The auction is not closed (i.e., bidders can enter and bidders can leave).

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• There are always budget constraints, cash-flow issues, or volume constraints for some, if not all, of the advertisers, which limits the amount of keyword advertising spend available. • There are always other keyphrase options. • There is a variety of keyphrase matching options that affect the valuation of a click, and therefore the bid, of a keyphrase. • There are other advertising options beside sponsored search, which affects the bid price at a given moment in time. Relating Theory to Practice • Using various combinations of expected clicks per bid and CPC per bid, determine your optimal bid (i.e., the bid that optimize profit). Bidding above the optimal bid will reduce overall profits. Bidding under the optimal bid will leave profitable clicks on the table. • There are multiple reasons beside profit for bidding on a keyphrase, including aspects such as branding. For example, there are also advantages in occupying screen real estate on the SERP if the cost imposed on your competitors is more than the cost you pay for occupying the ad position. Identify keyphrases where you would bid slightly above your optimal bid to impose added cost on your competitors (i.e., your absolute decrease in profits is less than the competitor’s absolute increase in CPC). • Rarely is any product tied to just one keyphrase. More often, there are several keyphrases and match types impacting a product, requiring a portfolio perspective (i.e., examining the entire collection of keyphrases for a product). As you monitor keyphrase bids, note the possible impacts that these changes are having on ROA for other keyphrases. Sometimes, increasing the performance of one keyphrase may actually reduce overall returns for the entire keyphrase collection. Conclusion In this chapter, we discussed the auction mechanism that underlies sponsored search. It is the economic engine of sponsored search, which is the economic engine of the Web. The auction portion is a keyword-allocation process, where advertisers bid on keyphrases. However, these keyphrases are surrogates for the real item of value€– ad positions. The keyphrases are really limitless, but the ad positions are a scare commodity limited to the SERP screen real estate. Because the space for ads is limited, there is a ranking of positions from best to worst. The keyword auction is rather straightforward. The advertisers, acting as bidders, state bid prices for keyphrases. Using a mechanism known as the GSP auction, the search engine accesses the bids and charges the top bidder the price of the second-highest bid plus a small delta. The second-highest bidder pays the price of the third-highest bidder plus a small delta, and so forth. This occurs for all bidders. Based on this ranking of bidders, one can easily develop a ranking of ads from these advertisers.

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However, in the overall sponsored-search auction, additional elements come into play. First, the CTR of the keyphrase-ad-landing page combination affects the ad’s placement. This is referred to as quality score. If an ad has gotten good CTR rates in the past, then that ad may be ranked ahead of an ad with a higher bid but lower CTR. Although the allotment mechanisms vary, comparing quality scores lead to an online auction model where the general principles of the GSP still hold. The sponsored-search auction model has had some criticism, most notably that the keyword auction is not theoretically stable, although many of these analyses are based on some nonrealistic assumptions. Additionally, there have been criticisms that the search engine, as market maker, has a built-in incentive to maximize profit for itself at the expense of the bidders in the auction. This is true, although advertisers could just take their advertising dollars elsewhere, given that the marketplace is open. The overall effect of economic assignment of value by the advertisers and marketplace determination by consumers has led to an effective online advertising process where the search engine, advertisers, and consumers are served and rewarded. Let us now review, in an integrated fashion, all the disparate components of sponsored search. References ╇ [1] Levy, S. 2009. “Secret of Googlenomics: Data-Fueled Recipe Brews Profitability.” Wired Magazine, Retrieved April 4, 2011, from http://www.wired.com/culture/culturereviews/ magazine/17–06/nep_googlenomics ╇ [2] Doyle, R. A. and Baska, S. 2002. “History of Auctions: From Ancient Rome to Today’s HighTech Auctions.” Retrieved April 4, 2011, from http://www.absoluteauctionrealty.com/history_ detail.php?id=5094 ╇ [3] Peterson, K. 2006. Microsoft’s adCenter Is Google, Yahoo! Rival. (May 4). The Seattle Times, http://seattletimes.nwsource.com/html/businesstechnology/2002970721_microsoft04.html. ╇ [4] McAeee, R. P. and McMillan, J. 1987. “Auctions and Bidding.” Journal of Economic Literature, vol. 25(2), pp. 699–738. ╇ [5] Krishna, V. 2002. Auction Theory. San Diego, CA: Academic Press. ╇ [6] Varian, H. R. 2007. “Position Auctions.” International Journal of Industrial Organization, vol. 25(6), pp. 1163–1178. ╇ [7] Surowiecki, J. 2004. The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations. New York: Random House. ╇ [8] Jansen, B. J. and Mullen, T. 2008. “Sponsored Search: An Overview of the Concept, History, and Technology.” International Journal of Electronic Business, vol. 6(2), pp. 114–131. ╇ [9] Zhou, Y. and Lukose, R. 2006. “Vindictive Bidding in Keyword Auctions.” In Second Workshop on Sponsored Search Auctions, Conference on Electronic Commerce (EC’05), Ann Arbor, MI. [10] Edelman, B. and Ostrovsky, M. 2007. “Internet Advertising and the Generalized Second Price Auction: Selling Billions of Dollars Worth of Keywords.” American Economic Review, vol. 9(1), pp. 242–259. [11] Urbany, J. E., Dickson, P. R., and Wilkie, W. L. 1989. “Buyer Uncertainty and Information Search.” Journal of Consumer Research: An Interdisciplinary Quarterly, vol. 16(2), pp. 208–215. [12] Rosso, M. A. and Jansen, B. J. 2010. “Brand Names as Keywords in Sponsored Search Advertising.” Communications of the Association for Information Systems, vol. 27(1), Article 6. [13] Goldman, E. 2010. Google Gets Complete Win in Rosetta Stone Case. (August 4). Retrieved February 2, 2011, from http://blog.ericgoldman.org/archives/2010/08/google_gets_com.htm

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[14] Brooks, N. 2004. The Atlas Rank Report I: How Search Engine Rank Impacts Traffic. (July). Retrieved August 1, 2004, from http://www.atlassolutions.com/uploadedFiles/Atlas/Atlas_ Institute/Published_Content/RankReport.pdf [15] Brooks, N. 2004. The Atlas Rank Report II: How Search Engine Rank Impacts Conversions. (October). Retrieved January 15, 2005, from http://www.atlassolutions.com/pdf/ RankReportPart2.pdf [16] Athey, S. and Nekipelov, D. 2010. A Structural Model of Sponsored Search Advertising Auctions (working paper). (May). Retrieved February 2, 2011, from http://www.stanford.edu/ group/SITE/SITE_2010/segment_3/segment_3_papers/nekipelov.pdf [17] Advertising Age 2005. “38 Years of Super Bowl Ad Stats.” In Advertising Age: Advertising Age. [18] Associated Press. 2010. “Super Bowl Ad Prices Dip, but Still Pricey.” In CBS News Sports. [19] Shah, S. 2010. Analyze This: The Subtle Science of Bidding, Part 1: The Real Story. (June 18). Retrieved January 19, 2011, from http://searchengineland.com/the-subtle-science-of-biddingpart-2-brand-keyword-management-45387 [20] Shah, S. 2010. Analyze This: The Subtle Science of Bidding, Part 2: Brand Keyword Management. (July 16). Retrieved January 19, 2011, from http://searchengineland.com/thesubtle-science-of-bidding-part-2-brand-keyword-management-45387 [21] Shah, S. 2010. Analyze This: The Subtle Science of Bidding, Part 3: Second Order Effects. (August 13). Retrieved January 19, 2011, from http://searchengineland.com/the-subtle-scienceof-bidding-part-3-second-order-effects-46983 [22] Lahaie, S. 2006. “An Analysis of Alternative Slot Auction Designs for Sponsored Search.” In 7th ACM Conference on Electronic Commerce, Ann Arbor, MI, pp. 218–227. [23] Libby, B. (2010). Search Marketing Advice from Machiavelli. Retrieved January 19, 2011, from http://www.thesearchagents.com/2010/07/search-marketing-advice-from-machiavelli/ [24] Ostrovsky, M. and Schwarz, M. 2009. Reserve Prices in Internet Advertising Auctions: A Field Experiment (Research Paper No. 2054). (December 24). Retrieved February 2, 2011, from http://ssrn.com/abstract=1573947 [25] Ausubel, L. M. and Milgrom, P. 2006. “The Lovely but Lonely Vickrey Auction.” In Combinatorial Auction, P. Cramton, Y. Shoham, and R. Steinberg, Eds. Cambridge, MA: MIT Press, pp. 17–40. [26] Rothkopf, M. H. 2007. “Thirteen Reasons Why the Vickrey-Clarke-Groves Process Is Not Practical.” Operations Research, vol. 55(2), pp. 191–197. [27] Aggarwal, G., Goel, A., and Motwani, R. 2006. “Truthful Auctions For Pricing Search Keywords.” In 7th ACM Conference on Electronic Commerce, Ann Arbor, MI. [28] Cary, M., Das, A., Edelman, B., Giotis, I., Heimerl, K., and Karlin, A. R. 2007. “Greedy Bidding Strategies for Keyword Auctions.” In 8th ACM Conference on Electronic Commerce (EC’07), San Diego, CA, pp. 262–271. [29] Lahaie, S., Pennock, D., Saberi, A., and Vohra, R. 2007. “Sponsored Search Markets.” In Algorithmic Game Theory, R. Nisan and V. Tardos, Eds. Cambridge: Cambridge University Press, pp. 4–25. [30] Nash, J. 1950. “Equilibrium Points in N-Person Games.” Proceedings of the National Academy of Sciences, vol. 36(1), pp. 48–49. [31] Nash, J. 1951. “Non-Cooperative Games.” The Annals of Mathematics, vol. 54(2), pp. 286–295. [32] Easley, D. and Kleinberg, J. 2010. Networks, Crowds, and Markets: Reasoning About a Highly Connected World. Cambridge: Cambridge University Press. [33] Feng, J., Bhargava, H., and Pennock, D. M. 2007. “Implementing Sponsored Search in Web Search Engines: Computational Evaluation of Alternative Mechanisms.” Informs Journal on Computing, vol. 19(1), pp. 137–148.

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Bringing It All Together in a Framework of Sponsored Search

Whenever a theory appears to you as the only possible one, take this as a sign that you have neither understood the theory nor the problem which it was intended to solve. Karl Popper, considered one of the most influential philosophers of science in the twentieth century [1].

While implementing a sponsored-search effort for our framing business, we must address many aspects that consume our attention, including keyphrase selection, ad creation, market research, insight into the consumer as both a searcher and a customer, elements of branding for our product, advertising and marketing concepts, and bidding strategies. These aspects may seem like a list of separate components that you somehow make fit into this thing called “sponsored search.” But although we discuss them separately, the separation is artificial. Each of these elements is totally integrated into the complete picture of a sponsored-search effort. The separation is an artifact of the discussion, as a method of simplification. In real life and practice, one cannot select keyphrases without understanding the market and the potential consumer. One cannot design an advertisement without an understanding of cognitive, affective, and situational aspects of the customer. One cannot begin marketing without understanding the product attributes. One cannot develop advertisements that get results without understanding the customer and the bidding process. One cannot bid effectively without understanding measurement and metrics and competition. It is a lot to deal with and become an expert in! Moreover, it is all related. Potpourri: People have a tendency to overestimate what they know. More accurately, people put more faith in the concept of what they know than they really [1]. should. This is related to the caution stated by Popper in the epigraph [1 1]. We do this individually and also in groups and in society. So, we should expect it with our views of the foundational elements of sponsored search and even the implementation aspects. (Continued) 203

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The one thing that we mostly know about scientific theories and models is that they are eventually proven incorrect. This is not just true for “science back in the old days.” It is happening now with our current theories and paradigms. One of the most interesting examples to illustrate this is known as Schrödinger’s cat paradox, which is a thought experiment to expose the bizarreness of, and perhaps incorrectness of, quantum mechanics. Basically, a cat is put in a box where there is poison in a flask, a radioactive source, and a Geiger counter that releases the poison if radiation is detected. The paradox is this. Mathematically, there becomes a stable period (i.e., more than a moment, an enduring and stable time) where, according to quantum [2]. mechanics, the cat is both dead and alive [2 2]. Quantum mechanics may be correct. Still, you should approach all theories and models with a skeptical eye. All the disparate components are related and form an integrated whole that is sponsored search. Where in previous chapters we dealt with each component separately, let us now bring it all together and look at the entire sponsored-search system. We first looked at the theoretical basis for this totality view, which is general systems theory. Then, we examine the sponsored-search system, focusing on the interactions inherent within. General Systems Theory Much of science is focused on dissecting a complex system into its fundamental components, which is what we’ve done with our review of sponsored search so far. A system, such as sponsored search, can be divided into its individual components so that each component can be analyzed as an independent entity. One can also add the components in a linear fashion to describe the totality of the system. Both are reductionist approaches that look internally and examine the subsystems within the system. These classic reductionist view of science permits focused analysis of foundational concepts. However, there is an alternate view that focuses on the whole system, known as general systems theory [3]. According to general systems theory, conceptions of reduction are incorrect, at least at times. Instead, in general systems theory, a system is characterized by the interactions of its components and the nonlinearity of those interactions. In other words, we take the totality and the complexity of interactions into account simultaneously. Potpourri: General systems theory has a lot in common with chaos theory and complexity theory. Chaos theory addresses the study of complex dynamical systems (i.e., systems that follow a fixed rule over time), where the system is highly dependent on

Bringing It All Together

initial conditions. This means that very slight fluctuations in the initial conditions can radically affect the end state of the system. So, a ball balancing on a hilltop (using the classic example) may fall in many directions depending on very slightly changing atmospheric conditions. Known commonly as the butterfly effect, these small changes in initial conditions make long-term prediction impossible. However, a chaotic system is not random. These systems are dynamical so their future state is determined by the initial state. These systems only appear to be random because slight changes are amplified so much over time. So, how do we address chaotic systems? We continually sample data and measure the system to do short-term predictions. For example, we might not be able to predict what the weather will be two months from now, but we can predict with good accuracy what the weather will be in two hours. According to this view of systems, knowing one part of a system enables us to know something about another part. In general systems theory, rather than a linear approach, we analyze systems using two approaches: r
Cross-sectional approach deals with the interaction within a system. r
Developmental approach deals with the changes in a system over time. Specifically for us, we are concerned with elements and patterns within the sponsoredsearch effort, the foundational components of sponsored search, and the interdependence within the sponsored-search system. We are interested in the temporal aspects of sponsored search, such as the auction process. So, we are both concerned with sponsored search in a cross-sectional perspective and a developmental perspective. What follows are more precise definitions of critical terms in general systems theory: r
Element – any identifiable entity within a system r
Pattern – any relationship of two or more elements r
System – any pattern whose elements are related in a sufficiently regular way to justify attention r
Component – any interacting element in an acting system r
Interaction – a situation where a change in one component induces a change in another component r
Interdependent – a situation where a change in an element induces a change in another element. We will use these terms as we take an integrated view of sponsored search. General Systems View of Sponsored Search Figure 9.1 illustrates the general framework of the sponsored-search system. The sponsored-search system is composed of foundational and structural components. Cutting across these structural and foundational components are inherent constructs,

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Inhernet Constructs

Consumers

Keyphrases

Advertisements

Principle of least Principle of least effort effort

Principle of least effort

Human information Human information behavior behavior

Relevance

Human information processing

Human information processing

Bidding

Measurement

Relevance Auction theory

Power law

Power law

Hick-hyman law

Buying funnel

Information obtainability

Information obtainability

Trace data

Signaling theory

Unobtrusive method

Serial position effect

Behavioralism

Decision making Uncertainty principle Communication User intent process

Nash equilibrium

Recency effect Branding Advertising Marketing Foundational Elements

Figure 9.1. Framework of the general systems view of sponsored search with foundational elements, structural elements, and inherent constructs.

which is the third component. Each of these components is composed of elements that interact with one another in complex patterns. There elements are interdependent, as shown in the cross-section view of Figure 9.1. Let us review sponsored search from this integrated framework. Potpourri: In the book The 100: A Ranking of the Most Influential Persons in History, Michael H. Hart ranks one hundred most influential people in human [4]. history, along with some honorable mentions [4 4]. Hart does a statistical analysis using attributes of the people on the list, noting that there is a clustering by location and time. Hart credits this clustering to particular societies’ ability to communicate more effectively. This increased ability to communicate has a positive effect on the society’s ability to innovate. With this viewpoint, sponsored search (as the economy engine of the Web) is a significant social enhancer. Given that Google was the search platform that really took the sponsoredsearch concept and made it the economic engine of the Web, Sergey Brin and Larry Page really deserve credit for shaping the Web and Internet as we know it. Their efforts were most influential. By the way, there were two other interesting correlations that Hart discovered with the people on his list: There were high occurrences of gout and no living descendents. Nothing to do with sponsored search, but I found it interesting.

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Foundational components are those components that provide the base concepts and elements for sponsored search as an e-commerce endeavor, specifically branding, advertising, and marketing. They impact all structural components. Structural components are those elements that form the building blocks of the sponsored-search process, including the consumers, the keyphrases that link advertisements to the query terms, the online auction bids, the advertisements, and the analytics that provide the measurement of the overall process. They are all impacted on by the foundational components and are defined, in terms of interaction patterns, by the inherent constructs. Inherent constructs are those concepts that collectively form a theoretical view of sponsored search. They set the groundwork for modeling sponsored search or any of its subsystems. Let us examine each of these components further, beginning with branding, advertising, and marketing. Foundational components The elements of branding, advertising, and marketing are the basis of the sponsoredsearch system as it relates to the business or organization for which the sponsoredsearch effort exists. Branding.╇ A brand is the identity of a specific product, service, or business. A brand can take many forms, including name, sign, symbol, color combination, or slogan. A legally protected brand name is called a trademark. The larger concept of a brand can encompass identity, as the brand affects the perceived personality of a company, product, or service. The act of branding usually involves the repetition of an image, slogan, or product name within a message to get consumers to associate related qualities with the brand. Branding is a key element of the sponsored-search system in that sponsoredsearch efforts, especially advertisements, are continually reinforcing the business’s brand in the mind of the searcher. Advertising.╇ Advertising is a form of commercial communication with the intent to persuade a targeted audience (i.e., consumers or potential customers) to purchase or take some action regarding products or services. These products or services are related to a brand, and the specific communication is encapsulated in a message known as an advertisement. Advertising is commercial because the communication is usually paid for or identified through one or more message sponsors (i.e., advertisers). The consumer views the advertisement via some media where they know or at least are alerted to the fact that the message is paid for by an advertiser. Through the communication process of advertising, advertisers typically seek to generate increased consumption of a product or service. Advertising is a key element of the sponsored-search system in that the principles of advertising are directly applicable to sponsored-search advertisements in terms of crafting ad copy and appealing to potential customers.

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Marketing.╇ Marketing is the process by which a company attempts to create customer interest in its products or services. It generates the strategy that underlies sales techniques (i.e., advertising), business communication (i.e., branding), and business development (i.e., new products and services). Therefore, marketing is an integrated process through which a company builds positive consumer relationships and creates value for both the consumers and the business. Marketing identifies potential customers, satisfies the existing customers, and works to generate repeat customers. With the customer as the focus of its activities, marketing is one of the major components of any business. The main goal of a marketing strategy is to keep the business profitable. Marketing is a key element of the sponsored-search system in that sponsored search is a direct form of communication with the consumer and potential marketing segments. Structural components The structural components provide the compartmentalized aspects of sponsored search, including the consumer, keyphrases, advertisements, bidding, and measurements. Consumer.╇ A consumer is any person that may potentially use a product or service from a business, although the concept occurs in different contexts and domains, so the nuanced usage of the term may vary. Businesses may be concerned with several target demographics. These concerns typically focus on variables aimed toward a buy/not-buy decision of the consumer. Therefore, the aspect of consumer decision making-process is inherently a key element of sponsored search. Consumers are key elements of the sponsored-search system. Consumers have varying levels of prior knowledge of a business’s products and services, including product attributes such as price. Therefore, the search engine is an intermediary between the business and consumers. Advertisers choose which keyphrases they want to target, and consumers enter keywords into search engines to search through the links that appear on the SERP. The goal for the advertiser is to target consumers in the least expensive, most effective manner. Consumers want to minimize the search costs involved with finding an acceptable product or service. If advertisers choose their keyphrases well, the consumer receives relevant advertisements. Thereby, the costs for both are reduced. Keyphrases.╇ From a linguistic perspective, a keyword is a term or set of terms that occurs in a collection of texts more often than we would expect by chance alone. One calculates a keyterm using a statistical test, typically log linear, by comparing the word frequencies in a text against their expected frequencies derived in a much larger corpus, which acts as a reference for general language use. Keywords are those in a collection of queries that relate queries to keyphrases selected by advertisers to trigger sponsored-search ads. Keyphrases are critical elements of the sponsored-search system in that they tie the advertisement to the searcher and hopefully convert this searcher into a potential customer. Therefore, the keyphrase has to trigger a relevant advertisement that transitions the searcher into the customer phases of the online interaction.

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Bidding.╇ Bidding is the making of an offer, typically within the confines of a competitive auction. A price offer is called a bid, the term generally used in sponsoredsearch auctions. In sponsored-search systems, given the amount of online content and searches, automated bidding systems typically handle the bids from advertisers. The minimum bid or needed bid is typically done via a cost-per-click (CPC) bidding model, although other methods can be used, such as cost per impression, cost per mille (thousand) (CPM), or cost per action (CPA). However, the CPC option seems like the most balanced option. The CPM option is biased toward the publisher, and the CPA option is biased toward the advertiser. One can expect that a certain mix of these models will coexist within automated bidding systems, depending on the practical consideration of both sides. We also see these bidding auctions moving toward cost/value economic equilibrium overall and for advertisers specifically. With the maturing and adoption of the Internet as an advertising platform by most advertisers in the world, more and more online advertising segments are reaching economic equilibrium. In other words, the price tag of click/impression/action is approaching the mean value of the click/ impression/action to advertisers. This lowers the opportunities for click arbitrage and very cheap client acquisition, which is a characteristic of a mature market. Bidding is a key element of the sponsored-search system in that it directly links the sponsored-search effort to the bottom line, revenue, and profit. Advertisements.╇ An advertisement is a paid announcement, typically for some type of product or service, but it can also be for a business or organization. The goal of an advertisement is generally to increase consumption of a product or use of a service, even if indirectly, via branding communication. Advertisements communicate some information to consumers. This information usually includes the name of a product or service and how that product or service benefits the consumer. Advertisements are key elements of the sponsored-search system in that these are the messages that transition the person from role of searcher to role of consumer. Measurements.╇ Sponsored-search analytics are about measurements. Measuring is the process of determining the magnitude of a quantity, such as length or mass, relative to a unit of measure. Measurement is the specific result obtained from the measuring process. For example, Web analytics is the measurement, collection, analysis, and reporting of Internet data for purposes of understanding and optimizing Web usage. Sponsored-search analytics is a process for measuring keyword advertising traffic for business and market research. Typically, this measurement is directly in sponsored-search efforts. Sponsored-search analytics applications can also assist businesses in measuring the results of integrated marketing campaigns, such as print advertising campaigns, by estimating how traffic changed after the launch of a new advertising campaign. Sponsored-search analytics provide data on the number of keyphrase searches, number of ad impressions, number of clicks, return on investments, and so on. Sponsoredsearch analytics can also be leveraged to find popularity trends of keyphrases for market research purposes.

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Measurement is a key element of the sponsored-search system in that it allows for analysis, reflection, evaluation, and improvement in the next round of planning and implementation. Inherent constructs Inherent constructs are the building blocks that explain aspects of sponsored search as a system. These theoretical building blocks collectively form a theoretical view of sponsored search and set the groundwork for modeling sponsored search or any of its subsystems. As shown in Figure 9.1, some of these constructs apply primarily and directly to more than one structural components, and all are related to foundational components. The inherent cross-cutting constructs of sponsored search are: • Auction theory: how people act in an auction, viewing the auction as a game. Auction theorists typically focus on issues such as the efficiency of a given auction design (i.e., how well the auction achieves the goals of all parties in the auction, including the auctioneer), optimal and equilibrium bidding strategies, and effectiveness of the auction in terms of revenue generation. In classical auction theory, participants are interested in maximizing their own situation without considering others. Auction theory, specifically the General Second Price auction, is the background for most sponsored-search auctions. (Element of Bidding component.) • Behaviorism: an analytical approach that emphasizes the outward behavioral aspects of thought. Behaviorism, as defined for sponsored search, emphasizes the observed behaviors without discounting the inner aspects that may accompany these outward behaviors. This more accommodating outlook of behaviorism supports the viewpoint that one can gain much from studying expressions (i.e., behaviors) of users when interacting with advertising campaigns. These expressed behaviors may reflect aspects of the searcher’s inner cognitive factors but also contextual aspects of the environment within which the behavior occurs. In sponsored-search analytics, we are concerned with behaviors. (Element of Measurement component.) • Buying funnel: a staged process for describing the way consumers make their buying decisions, from becoming aware of a need all the way to the final purchase of a product or service that addresses the need. There are various labels for each stage; one common labeling system is Awareness, Research, Decision, and Purchase. The buying funnel helps explain consumer searching behavior. (Element of Consumer component.) • Communication process: conveys a message (i.e., information) to someone. A sender, a message, a channel of communication, and a receiver are involved. Challenges of communication processes include accurately conveying the message to the receiver. The communication process provides the explanation for the exchange between the searcher and the advertiser. (Element of Consumer component.) • Consumer decision making: usually presented as a hierarchical staged model consisting of one or more prepurchase, purchase, and postpurchase phases. The

Bringing It All Together

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prepurchase phases include need recognition, information search, evaluation of alternatives, and product choice. Consumer decision making assists in explaining the consumer purchasing process. (Element of Consumer component.) Hick-Hyman Law: a formula for calculating the time it takes for a person faced with a set of choices to make a decision. The Hick-Hyman Law is impactful on advertisements. (Element of Advertisements component.) Human information behavior: the totality of human behavior in relation to sources and channels of information, including both active and passive information seeking and information use [5]. Human information processing primarily affects consumers and keyphrases. (Element of Consumer and Keyphrase components.) Human information processing: the method of acquiring, interpreting, manipulating, storing, retrieving, and classifying recorded information [6, 5]. (Element of Keyphrase and Advertisements components.) Information foraging theory: an application of signaling theory in Web search. Information foraging states that humans adopt adaptive strategies to optimize their intake of useful information per unit cost. Related to signaling theory that explains advertisement development. (Element of Advertisements component.) Information searching: refers to people’s interactions with information-retrievalsystems, ranging from adopting search strategy to judging the relevance of information retrieved [5]. Human information processing primarily affects keyphrases and advertisements. (Element of Consumer, Keyphrases, and Advertisements components.) Nash equilibrium: a concept in game theory strategy. It refers to a “point” in the “game” where all players in the game have nothing to gain by changing their strategy. Hence, the game is in equilibrium and, therefore, stable. Stability is a key component for online auctions, such as those associated with sponsored search, and allows advertisers to develop rational advertising plans. (Element of Bidding component.) Power law: a special kind of mathematical relationship between two quantities. When the frequency of an event varies as a power of some attribute of that object, the frequency is said to follow a power law. A power is an exponent: a mathematical notation indicating the number of times a quantity is multiplied by itself. An attribute of an object can be, for example, its size, its rank, or its height. Like the standard bell curve, the power law is a probability distribution. Power laws can explain consumer behaviors and keyphrase selection where there are few elements that occur very frequently (i.e., the head) and a whole bunch of elements that occur very infrequently (i.e., the tail). (Element of Consumer and Keyphrases components.) Principle of information obtainability: the more accessible the information, the more likely it is that people will use that information. The construct of information obtainability impacts keyphrases and advertisements. (Element of Keyphrases, and Advertisements components.) Principle of least effort: an organism generally seeks a method involving the minimum expenditure of energy [7]. The principle of least effort impacts consumers, keyphrases, and advertisements. (Element of Consumers, Keyphrases, and Advertisements components.)

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• Principle of uncertainty: earlier stages of information searching are initiated by a lack of understanding or limited knowledge [8]. The uncertainty principle impacts keyphrases. (Element of Consumer, Keyphrases, and Advertisements components.) • Recency effect: humans tend to remember the last few items they see as compared to those intermediately ranked items. The recency effect addresses why the advertisement at the end of the list get high numbers of clicks. (Element of Advertisements component.) • Relevance: how pertinent, connected, or applicable something is to a given matter. Relevance impacts advertisements and bidding, although it is also tied to keywords and consumers. (Element of Advertisements and Bidding components directly, but also subsumed within human information behavior and human information processing.) • Serial position effect: a position’s impact on various human behaviors. Serial position effect helps explains the effect of rank on advertisements, with the advertisements in the first position on the list getting most of the clicks. (Element of Advertisements component.) • Signaling theory: searchers often use clues in the decision-making process that guide perceptions of cost, benefits, rewards, and risks associated with choices [9]. (Element of Advertisements component.) • Trace data: the traces, remains, or wear produced by processes in which people conduct the activities of their daily lives. These processes often create things or marks, or reduce some existing material. Within the confines of research, these things, marks, and wear become data. The trace data from logging software is the interactions between searcher, search engines, and Web sites. This trace data then becomes the data for sponsored-search analytics. (Element of Measurement component.) • Unobtrusive method: analytical practices that do not require the analyst to intrude in the context of the actors. Unobtrusive methods do not involve direct elicitation of data from those being observed. Sponsored-search analytics leverage the unobtrusive method of data collection. (Element of Measurement component.) Foundational Takeaways • Sponsored search is an integrated system with structural, foundational, and inherent components. • These components are composed of several elements that are key constructs of sponsored search. • To understand the details of sponsored search, we take a reductionist approach by examining individual components and elements. • To understand the big picture of sponsored search, we take a general systems approach and examine the system from a cross-sectional and developmental perspective. Relating Theory to Practice Figure 9.1 is a generalized concept of the entire sponsored-search system. However, we can take this general framework and apply it at a particular level, focusing in on

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more practical details. Take the sponsored-search system framework in Figure 9.1 and apply it to your account. • What are the unique and particular elements within the overarching structural and foundational components? • How are you implementing the inherent constructs for your vertical? • What specific patterns can you detect in your sponsored-search efforts, especially in the areas of bidding, keyphrases, and advertisements? Conclusion A general systems view of the sponsored-search system integrates structural and foundational components. We examine elements of the inherent cross-cutting component of sponsored search, including human information behavior, human processing theory, information searching, relevance, principle of least effort, principle of uncertainty, principle of information obtainability, Hick-Hyman Law, Power law, signal theory, information foraging theory, serial position effect, recency effect, buying funnel, consumer decision making, communication process, behaviorism, auction theory, and the Nash equilibrium. Foundational components include the elements of branding, advertising, and marketing. Structural components include the elements of consumer, keyphrase, bidding, advertisement, and measurement. Web search engines are indispensable tools for interacting on the Web. In addition to addressing information requests, modern Web search engines are navigational tools that take people to specific Web sites or aid in browsing. People also employ search engines as applications to carry out e-commerce transactions. People continue to employ search engines in new and increasingly diverse ways, and search engines are constantly trying to improve the retrieval aspects of their services. One novel innovation for improving Web retrieval has been sponsored search. With sponsored search, major Web search engines such as Yahoo!, Microsoft Bing Google, and Ask have significantly altered online commerce. Battelle provides an overview of the factors that have led to the development of these sponsored Web search platforms [10]. Within the confines of this Web environment, sponsored search has made an enormous impact on the accessibility of information and services on the Web. Sponsored search has played a critical role in supporting access to the many free services provided by search engines (i.e., spell-checking, currency conversion, flight times, desktop searching applications, etc.) that have rapidly become essential to so many Web users. Without the workable business model of sponsored search, it is doubtful if the major Web search engines could finance anything close to their current infrastructures. These infrastructures provide the capability to crawl billions of Web pages; index several billion documents including text, images, videos, newspapers, blogs, and audio files; accept millions of Web queries per day; and present billions of links per week. Sponsored search has also provided a workable business model for metasearch engines, which are beneficial for searchers needing high recall and requiring a thorough coverage of a topic.

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Sponsored search additionally provides an effective method for overcoming the inherent biases in the technical implementation of particular Web search engines [11], as well as allowing content providers to move their links to the first SERP at a relatively low cost. In doing so, sponsored search is an essential tool vital to the success of many businesses. It is fair to say that without sponsored search, the Web search engine market€– and the Web!€– would look far different than it does today. However, it appears that nothing remains the same on the Web. So, we can expect sponsored search to evolve in the future. In the next chapter, we look at possible changes to sponsored search and the drivers of these changes. References ╇ [1] Popper, K. 1972. Objective Knowledge: An Evolutionary Approach. Oxford: Oxford University Press. ╇ [2] ErwinSchrödinger (Translated by John D. Trimmer). 1980. “The Present Situation in Quantum Mechanics: A Translation of Schrödinger ‘Cat Paradox Paper’.” Proceedings of the American Philosophical Society, vol. 124(1), pp. 323–338. ╇ [3] vonBertalanffy, L. 1976 [1956]. General System Theory: Foundations, Development, Applications. New York: Braziller. ╇ [4] Hart, M. H. 1992. The 100: A Ranking of the Most Influential Persons in History. New York: Citadel Press. ╇ [5] Wilson, T. D. 2000. “Human Information Behavior.” Informing Science, vol. 3(2), pp. 49–55. ╇ [6] Putrevu, S. 2002. “Exploring the Origins and Information Processing Differences between Men and Women: Implications for Advertisers.” Academy of Marketing Science Review, vol. 10(1), Article 1. ╇ [7] Zipf, G. K. 1949. Human Behavior and the Principle of Least Effort. Cambridge, MA: AddisonWesley Press. ╇ [8] Kuhlthau, C. 1993. “A Principle of Uncertainty for Information Seeking.” Journal of Documentation, vol. 49, pp. 339–355. ╇ [9] Gregg, D. G. and Walczak, S. 2010. “The Relationship between Website Quality, Trust and Price Premiums at Online Auctions.” Electronic Commerce Research, vol. 10(1), pp. 1–25. [10] Battelle, J. 2005. The Search: How Google and Its Rivals Rewrote the Rules of Business and Transformed Our Culture. New York: Penguin Group. [11] Introna, L. and Nissenbaum, H. 2000. “Defining the Web: The Politics of Search Engines.” IEEE Computer, vol. 33 (January), pp. 54–62.

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As we go forward, I hope we’re going to continue to use technology to make really big differences in how people live and work. Sergey Brin, cofounder of Google [1]

Hopefully, our framing shop’s products and services are matched to the desires and needs of the consumer market that our business is targeting, and our products are within the means of our consumers to purchase. However, the consumer market is an ever-shifting target. Technology changes drastically, altering our market analysis. Consumers may consider a product fashionable today but consider it out of fashion tomorrow. They may need a service today, but they may not need it when the context changes tomorrow. Needs of consumers are continually evolving as the array of products change. Competitors enter the market and often make our services obsolete or put price pressures on our business. Rarely does a business have a market to itself for any extended period of time. These are just some of the many pressures on businesses today. These concerns are all issues of change that our framing business must deal with to be successful. The technology, the consumer, and the context are in near-continual flux. It is the same with sponsored search, perhaps more so given the rapid pace of change on the Internet. Everything moves in Internet time! Predicting how technology, consumers, and context will change is fraught with difficulties, pitfalls, and limitations. However, by analyzing some harbingers currently present, we can make some general predictions for where sponsored search might develop in the near future. We examine this possible future by looking at aspects of technology, consumers, and context. Nonetheless, I believe the sponsored-search model, in pretty much its current form, will be the default keyword advertising model for the foreseeable future, although it will certainly add features and adapt to the ever-changing Internet environment. The core structure appears to be stable in the near term. This stability is partially due to the type of returns sponsored search is able to provide on the Web and Internet. No other revenue-generating platform currently can maintain the infrastructure of a search engine and related Web sites to the levels that 217

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sponsored search can generate. Additionally, no online advertising model has been as effective for so many different types of businesses as sponsored search. Sponsored search can also be effectively integrated with contextual and social advertising, enhancing its potential for longevity. However, the long-term potential for the future success of sponsored search depends on it continually adding value, both actual and perceived, to its stakeholders. As long as it does this better than the alternatives, its future is generally secured. Let us first take a quick look at these terms, value and stakeholders. From there, we will examine what changes the future might hold for sponsored search. Potpourri: Predicting the future is obviously not easy. Despite this, scientists are trying hard to do it, from predicting short-term events with social media streams to predicting longer-term threshold events. The Internet has aided in this effort with its extreme capacity for data collection. The problem with predicting the future using data from the past is described [2]. by Hume’s Problem of Induction [2 2]. Hume’s Problem of Induction questions whether one can predict that any event in the future will occur just because it occurred in the past. The induction problem entered pop culture via the book, The Black Swan, with [3]. the title being a classic example of induction from prior data [3 3]. For many years, it was widely believed that a black swan could not exist, because no European had ever seen one. Therefore, the prediction was that black swans cannot exist. However, black swans do exist, being native to Australia. Basically, in the end, we cannot prove that something will or will not occur just because it occurred or did not occur in the past. However, this does not mean that we cannot do anything with data. Scientists have gotten around this touchy point by using data only to disprove something. That is, empirically, we can show that there is evidence to disprove a hypothesis, but we cannot prove a hypothesis is true. The best we can say is that a hypothesis is supported based on the data. We see this in the warnings in the marketing literature of financial investments – “Past performance is not a guarantee of future success.” There is the related issue of that one cannot use data to prove a negative (i.e., that something does not exist). All we can say from data is that there is no evidence of something. Value and Stakeholders In Sergey Brin’s quote in the epigraph about using technology to make a difference, there are two concepts that we must define to evaluate whether or not a positive difference is being made. Namely, we must understand value and stakeholders. Value Value examines key questions, such as why goods and services are priced as they are, how the price of goods and services evolves, and how to calculate the correct price of goods and services.

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Value is a measure, evaluation, or estimate of the nature, quality, ability, extent, or significance of something. It is based on the theory of value. Value theory encompasses all the economic theories that attempt to explain the exchange worth or price of goods and services. Economically, the value of a product is the estimation by a consumer of that product. Value represents the relationship between perceived benefits relative to the perceived costs of acquiring benefits. It is often expressed as the equation: Value = Benefits / Cost Equation 10.1.╇ Value defined as a ratio of benefits to cost.

However, value has two components: subjective and actual. • Actual value holds that a product or service is worth what similar goods and services are worth. • Subjective value holds that for a product or service to attain economic value above zero, it must be useful in satisfying human wants or desires. Value is thus a function of consumers’ estimations, and relational to other goods and services. Therefore, the subjective value may have little to nothing to do with a product’s actual value, instead depending on the product’s ability to satisfy customer desires, needs, or requirements. One’s view of the value of sponsored search depends on their perspective and priorities. Stakeholders Stakeholders are people or organizations that have a vested interest in something, or would be affected by changes to it. There are three types of stakeholders: 1. Primary stakeholders are those ultimately affected, either positively or negatively. 2. Secondary stakeholders are “intermediaries,” that is, persons or organizations who are indirectly affected. 3. Key stakeholders have significant influence or importance. Key stakeholders can also belong to the first two groups. In evaluating a system, businesses typically do a stakeholder analysis, which is the process of identifying the individuals or groups that are likely to affect or be affected by a proposed action. Then, businesses order these stakeholders according to their impact on the action, and the impact the action will have on them. This information is used to assess how the business should address the interests of stakeholders in a project plan, policy, program, or other action. Value of sponsored-search stakeholders We can identify the value of sponsored search to the various stakeholders in the system. For the search engines, sponsored search has to continue to generate revenue to pay the bills. The rate of growth during the first decade of existence was truly phenomenal. Most technologies eventually stabilize, so one would expect sponsored search to do so also. However, there are many stable technologies that are solid revenue generators. As long as this is the case, sponsored search will provide value to the search-engine stakeholder.

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For the advertisers, including agencies, sponsored search must continue to be an online advertising system that is on par with or better than other advertising channels in terms of achieving results and business objectives. Sponsored search must continue to move products and services effectively and do it in an efficient manner for the business to generate a profit on these products and services. It must do this in absolute terms and also relative to other modes of consumer communication. Sponsored search must be easy to access and establish, at least for the small- and medium-size enterprises (SMEs), or there must be purchasable expertise available, particularly for larger enterprises. Drivers of Change For identifying the future, it is helpful to look at current problems, needs, and desires inherent in sponsored search. From this needs-and-problem analysis, you can expect advances in targeting, tracking, analysis, and optimization. You can expect that sponsored-search advertising will develop toward more control by the advertiser. Feature enhancement will continue in sponsored search. In the area of analytics, you will most likely see more nuanced and broader spectrum of analysis. In the marketing domain, consumers will most likely increase the time and money they spend online. Sponsored search is in flux [4]. There are confluxes of forces, or drivers, that are pushing, molding, and redefining the implementation of sponsored search. Let us now examine the possible future of sponsored search. Probable drivers of change include technology, consumers, and context. We address these as separate entities, but naturally, they are all interconnected. Technology Certainly, one driver of change is technology. Geo-location software.╇ Online check-in software, applications, and features create a remarkably compelling opportunity for brick-and-mortar businesses, especially those with a primarily localized market. With geo-location software, businesses can interact with online customers in a variety of creative ways that can impact sponsored search. When a customer announces that they are at a store or restaurant by checking in with a geo-location app, the business can shape and mold the customer experience in compelling ways before the customer even buys. A check-in by itself is of limited value, although it represents a customer in the door. To make check-ins really valuable, businesses need contextual, demographic, and situational data. With this information as feedback, a business, such as our framing shop, can target offers and recommendations in a way not possible with sponsored search in its current form. Integrating check-in type of software with sponsored search’s knowledge of a consumer’s desires and needs will give businesses the opportunity to leverage realtime contextual offers, discounts, and advertisements. These offers can directly shape a consumer’s behavior before any transaction occurs, which is an amazing convergence of online and offline interactions.

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It would be hard to imagine sponsored search not gaining some check-in type capability. Sponsored-search analytics.╇ With the increased use of check-in and mobile apps, one would expect to see geo-location-based metrics to measure the increase in foot traffic to brick-and-mortar stores based on sponsored-search advertisements, similar to click-to-call metrics now. Certainly, given the increased availability of consumer data, the future will hold sponsored-search metrics beyond impressions, clicks, and conversions. For example, the increasingly social aspects of Web sites, such as reviews and consumer comments, will likely lead to sentiment-analysis metrics that measure the tone of consumer comments about a brand or ad. This data can potentially affect how quality score is calculated. Already, sponsored-search platforms are offering searchers and consumers the ability to rate ads, so integration of reviews from other sites cannot be far behind. With the increase in tracking devices and use of the Web via many devices such as mobile phones, televisions, and navigation systems, advertisers will have simpler ways to measure the combined reach of television, Web, radio, and mobile advertising in an integrated marketing communication (IMC) approach. One can also foresee sponsored-search metrics that relate to user intentions and mental models in an effort to understand user goals and actions. From this type of data, one can better align advertisements or automatically adjust bids based on a determination of commercial intent. Development of such techniques will require complex data mining and analysis of user interaction data to identify the strength of associations among user clicks and actions. Current logging, analysis, and mining software can track these interactions. However, relating them to underlying user models to understand goals and intents, and doing so within an acceptable degree of accuracy, is not currently feasible within the sponsored-search domain. However, in other areas, such as blogging and microblogging [5], great strides have been made in this endeavor. It is also reasonable for planning tools to improve. For example, we can expect keyword tools that do not rely on just historical data but gather possible keyphrases from forum, blogs, review site comments, product reviews, customer e-mail messages, social media sites, and thesauruses. These will permit advertisers to increasingly speak the language of their customers. Based on their successes elsewhere, one would anticipate increased use of these techniques within sponsored search to extract the intentions of users and predict Web-searching behaviors. Click fraud control.╇ Click fraud counterefforts must continue to be improved. As new venues enter the sponsored-search domains, new potentials for click fraud also enter. Search engines must maintain a critical point of trust. Advertisers will stop using the sponsored system if click fraud worsens beyond some decisive point, just as merchants will flee a geographical area if shoplifting becomes too bad, making profitable operations impossible or transitioning to looting.

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Sponsored-search service providers must keep click fraud in check via more sophisticated technologies: • Prevention technology – stop click fraud from happening • Detection technology – catch click fraud once it occurs • Adjustment technology and processes – credit advertisers after click fraud is detected. This three-part effort of prevention, detection, and adjustment will call for greater transparency, increased communication, and more data sharing between the advertisers and sponsored-search platform providers. More sophisticated technology on the advertiser’s side will focus on microadvertising events, alerting them to unusual patterns. Given that click fraud and related activities have plagued sponsored search and other online advertising initiatives, it is doubtful that it is going away anytime soon. So, we must plan on dealing with it. Changes to query submission.╇ Probably the technique that most impacts sponsored search is changes to how the SERP is displayed in response to the query. Changing titles on the SERP, for instance from “sponsored results” to “sponsored ads,” can have an effect on searching behaviors. Changing small design aspects on the SERP, including lines, graphics, or borders that separate sponsored results from organic results, can change user behavior. Any technology that changes query submission beyond the traditional “enter a query and click submit” will most likely alter searcher behavior. The aspect of instant search is a good example. Instant search is a technology to make search more targeted and faster. Instant search combines predictive search with a real-time visualization of the results of that search. Instant search predicts what the searcher is searching for, allowing the searcher to not only see results faster, but also see the change in results while still typing. However, if results are displayed as someone types a query, and these results change with every additional letter typed, then instant search raises questions that strike at the core of sponsored search. Namely, how does one target for terms in transition? So, the keyphrase may be frames, but there are potential targets along the way for f, fr, fra, fram, and frame. Any change in the query-submission process that alters the display of the SERP will also affect sponsored-search behaviors. As the query is the major expression of need by the searcher, we should expect continued refinements and changes to the query-submission process. Mobile device and apps.╇ The effect of mobile technology is having a dramatic effect on how Web searching is conducted as well as introducing avenues of search that totally bypass the Web. The increased use of smart phones is having a dramatic effect on searching behavior, and hence a dramatic effect on sponsored search. A user with a mobile phone and appropriate app software can connect directly to e-commerce Web sites. Smart phones hold more personal information than personal computers, including name, number, and location. The increased ability of our devices to know

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our identities, locations, and desires will continue to affect how people search and therefore how advertisers will structure sponsored-search campaigns. For example, navigational queries are quite common on Web search engines, but they have a whole new meaning when executed on a mobile phone. A navigational search on a mobile phone may indicate an immediate desire to physically visit a business, for example. A similar issue occurs with product-related searches, with mobile apps existing just for product searches, including bar code readers and price checkers based on location. Similarly, as more and more retailers provide their own apps to searchers, people will be able to associate with brands directly, bypassing search engines and linking consumers directly with business Web sites. Sponsored-search services will have to adapt to this new mobile-app environment with advertisements on mobile phone platforms and with advertisements that integrate with the brand’s own app. Consumer Another driver of change for sponsored search is the consumer. Privacy concerns of online data.╇ With applications such as toolbars and apps on mobile phones, the ability to target consumers will certainly increase. We can already tell quite a bit about a potential mobile searcher [6]. However, there will be some point where consumers, or governments acting as regulatory agencies on their behalf, will draw the line. Although use of data from search and navigation can seem bland (i.e., I search for a book or browse a book Web site and then ads for this and related books start to appear), consumers can get creeped out by an “ad following them around” [7]. Most online consumers want three things concerning online privacy: 1. Control€– tell the consumer what you are doing and give the consumer the option to opt out (even if opting out means not using the service) 2. Obscurity€– use the consumer’s data mostly in the aggregate to detect trends and overall patterns 3. Anonymity€– even when the consumer’s data is individually isolated, protect and do not reveal the person’s identify. The use of consumer data will continue, especially with the increased use of mobile searching and the greater insight about the searcher that it contains. However, sponsored-search targeting methodologies will have to continually address consumer privacy concerns to avoid major consumer and legal backlash. Less computer use.╇ With the increased spectrum and availability of access to the Internet, there will be less use of browser-based Web access from a traditional computer. Consumers are increasingly stepping away from their desktop and laptop computers. As mentioned, they are searching from their phones or other devices. However, aspects such as Internet-based television, tablets, and gaming consoles are also Internet access points.

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Therefore, advertisers will need to expand their existing desktop-only targeted efforts to these other forms of access. There will be decreased revenue from the Web site on its own, and sponsored search will morph to fill these other forms of access. Mobile sponsored-search campaigns will most likely become the major revenue generators, with Web-based campaigns becoming secondary. Sponsored-search efforts need to adapt to a different consumer mindset for the mobile environment and non-computer environment. This new environment influences the entire search experience from aims to keywords to factors influencing these choices. For example, mobile search is often used to find the way to a property that the searcher already has in mind. Mobile search is often used by consumers on the move, either walking or in vehicles. Because of this, mobile searches use shorter queries and more navigational ones, so keyphrase selection and bidding strategies change. Integration of the online/offline worlds.╇ With the proliferation of check-in applications, local deal Web sites, mobile apps, Internet television, and micropayments, the blending of online and offline consumer data is gaining potential. We see this already occurring across services and devices. This integration is creating an increasingly accurate picture of consumers as individuals. Defining where offline ends and online begins is becoming increasingly difficult. Obviously, the use of apps and Web services on mobile devices will be the source of much of integration. However, computers and eBook readers, along with online databases, are also potential sources. Unfortunately, for marketers, the proprietary layers of this data are often stored inside individual services and applications; however, this data is increasingly shared among applications, usually with the permission of the consumer via the acceptance of third-party applications. In this melding of offline and online worlds, sponsored-search ads could increasingly incorporate the customer presence and behavior across the entire Web. With much behavior targeting already occurring, the next logical steps are the integration of behavior data from other sources besides searching. Context The final driver of change that we’ll discuss is the context in which the sponsoredsearch system operations. Real-time content.╇ Where once Web users visited a static Web page, people are now confronted with real-time content generated via review sites, blog comments, and status messages from social media sites [8]. Internet users’ increased engagement with real-time content [9] opens up interesting avenues for sponsored search, and it will obviously require structural changes. Real-time content is short-status message postings, sometimes with links to longer documents or multimedia content. Real-time content is typically generated on social networking and media platforms. Real-time content is normally created for the immediate temporal context, to be consumed as soon as produced rather than for

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archival intentions. Currently, advertising in the real-time content stream is a mix of keyword and contextual advertising, although there is much ongoing experimentation. Potentially, advertising in real-time content streams will use a combination of CPM, CPC, and CPA pricing models. Many questions concerning how relevant ads are integrated into real-time conversation flow, and on the SERP, still remain. As real-time content is integrated with the SERP, the searcher will be affected, although these effects are as yet undetermined. Real-time search on some of the major social media platforms already rival that of the major search engines. Therefore, one would expect to see sponsored-search-like models also on these searching platforms [9]. These services offer immediately interesting features such as local focus through geo-tagging postings, statuses, and other messages. Social media.╇ Certainly the growth of social media has and will impact sponsored search. Many social networking sites already have sponsored search integrated within their own advertising services. Soon, we will most likely see ads that are socially enabled, in that potential consumers will be able to share an ad, comment on an ad, and give feedback on an ad. It will increase the move away from advertisers talking to consumers directly and more to a two-way communication channel between a brand and its consumers. Searchers no longer have the sole expectation of searching to find information for a specific outcome when they go on the Internet, as the growth of interactions with social media shows [10]. As people spend more and more time connecting, sharing, and interacting with the social Web, they expect to interact with what they find in the search results. Time spent with the social Web involves many types of interactions with like-minded individuals in a community or network, one of which is looking for and sharing recommendations. This will be an exciting and challenging venue for sponsored search. Also, the blending with social media may introduce more push aspects to sponsored search. Keyword advertising is extremely good for converting people who are searching for information into consumers wanting to buy something. So, it is great for harvesting product demand but not particularly good for growing product demand. However, blended with a social element that can grow this demand, sponsored search can be even more effective. Alternative pricing models.╇ With the proliferation and diversification of sponsored search, from the Web [11] to mobile to real-time searching [9] to social media [10] to location-based services, it would seem that alternative pricing models beyond just CPC will gain popularity. One can see venues where CPM would apply, and in others where CPA seems most reasonable. With variations in pricing models along access venues, we will probably see more focused and targeted campaigns that may be mimicked across multiple platforms. Already, you can target similar sponsored-search campaigns to either Web or mobile, and even further target mobile campaigns to specific devices.

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Foundational Takeaways • The future of sponsored search depends on providing value to the stakeholders. • Changes in sponsored search will come from changes in technology, consumers, and context. • Expected changes will most likely be in the areas of mobile, social, metrics, and local. • Sponsored search is a people business, and people’s behaviors and attitudes are in a continual state of flux. Relating Theory to Practice For each of your accounts, ask yourself: • What additional sponsored-search metrics would you deem most appropriate? • Is geo-location software a technology that can impact your client’s business model? If so, how will it affect you sponsored-search effort? • Is click fraud a major concern for your client? What about in the years ahead? • What change to the query-submission process would most impact the advertisements for your account? • Is there a place in the mobile-app space for your sponsored-search effort? • Concerning search privacy, what is the minimal amount of data that you could collect and still reasonably target advertisements? • Will your sponsored-search effort transition to a mobile searching environment? • How well does your account integrate with both online and offline consumer activities? • Is there a place for real-time content in your sponsored-search effort? • Can social media play a role in achieving your account goals or taking your efforts in new directions? • Are there alternate pricing models that would be more beneficial in certain contexts? Conclusion We see a lot of forces at work on the sponsored-search concept. Intense forces from the mobile-apps area are changing the way people search for information. In this case, consumers are bypassing the Web and going to the Internet for search, and then back to the Web for the actual information. The use of mobile-app searching goes hand in hand with the increased focus on local search and search with a geographical focus. Mobile-app searching is also tied to the increased use of real-time content and social search, as people want information that is of importance here and now. These changes will affect sponsored-search analytics, increase personalization, and counter concerns for privacy. Although click fraud will continue, sponsored-search platforms will continue to combat it. Overall, it will be most likely contained, as advertisers become more selective in their Web site targeting.

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Regardless of these changes, the sponsored-search paradigm will be the dominant business model for search engines and the searching components of other major Web sites, including social media services, for the foreseeable future. There is nothing else on the horizon that more fully adds branding, advertising, and marketing value to the variety of stakeholders that sponsored search reaches. Since 1998, sponsored search has provided the revenue stream to finance the enormous technical infrastructure of the major search engines. As such, sponsored search has shaped the Web as we know it. The Web would be a vastly different place if it were not for sponsored search. It will be interesting to see where sponsored search takes us in the years ahead. However, for the foreseeable future, the constructs presented in this book might provide some element of continuity for those working in the field. References ╇ [1] Jennings, P. 2004. “Persons of the Week: Larry Page and Sergey Brin,” ABC News. Retrieved April 4, 2011, from http://abcnews.go.com/WNT/PersonOfWeek/story?id=131833&page=1 ╇ [2] Hume, D. 1910. An Enquiry Concerning Human Understanding. Cambridge, MA: P.F. Collier & Son. ╇ [3] Taleb, N. N. 2007. The Black Swan: The Impact of the Highly Improbable. New York: Random House. ╇ [4] Brinker, S. 2010. Agile Marketing for Conversion Optimization. (May 24). Retrieved January 26, 2011, from http://searchengineland.com/agile-marketing-for-conversion-optimization37902 ╇ [5] Jansen, B. J., Zhang, M., Sobel, K., and Chowdhury, A. 2009. “Twitter Power: Tweets as Electronic Word of Mouth.” Journal of the American Society for Information Sciences and Technology, vol. 60(11), pp. 2169–2188. ╇ [6] Jansen, B. J., Zhang, M., Booth, B., Park, D., Zhang, Y., Kathuria, A., and Bonner, P. 2009. “To What Degree Can Log Data Profile a Web Searcher?” American Society for Information Science and Technology 2009 Annual Meeting, Vancouver, British Columbia, pp. 1–19. ╇ [7] Helft, M. and Vega, T. 2010. “Retargeting Ads Follow Surfers to Other Sites.” The New York Times (August 29), p. A1. ╇ [8] Jansen, B. J., Chowdhury, A., and Cook, G. 2010. “The Ubiquitous and Increasingly Significant Status Message.” Interactions, vol. 17(3) (May–June), pp. 15–17. ╇ [9] Jansen, B. J., Liu, Z., Weaver, C., Campbell, G., and Gregg, M. forthcoming. “Real Time Search on the Web: Queries, Topics, and Economic Value.” Information Processing & Management. [10] Jansen, B. J., Sobel, K., and Cook, G. 2011. “Classifying Ecommerce Information Sharing Behaviour by Youths on Social Networking Sites.” Journal of Information Science, 60(11), 2169–2188. [11] Jansen, B. J. and Spink, A. 2005. “How Are We Searching the World Wide Web? A Comparison of Nine Search Engine Transaction Logs.” Information Processing & Management, vol. 42(1), pp. 248–263.

Glossary

Words are but the signs of ideas. Samuel Johnson, noted British poet and author credited with defining the English language [1]

This is a comprehensive glossary developed by leveraging and integrating glossaries from various organizations and terminology from academia, along with my own take on the field’s jargon to identify the key practitioner terminology on sponsored search and analytics. The end results is a combined, value-added glossary that identifies the key terminology of sponsored search from multiple perspectives. Some of the glossaries that served as references are: • • • • • • • • • • •

Advertising Glossary: http://www.advertisingglossary.net/ Business Dictionary: http://www.businessdictionary.com Marketing Terms: http://www.marketingterms.com/dictionary/a/ MiMi.hu: http://en.mimi.hu/marketingWeb/index_marketingWeb.html Quirks eMarketing Glossary: http://www.quirk.biz/resources/glossary/ Search Engine Dictionary: http://searchenginedictionary.com/ WebTrendsGlossary:http://www.Webtrends.com/Resources/WebAnalyticsGlossary. aspx WebMasterWorld http://www.Webmasterworld.com/glossary/index.htm Webopidia: http://www.Webopedia.com/ WhatIs.com Computer Dictionary: http://whatis.techtarget.com Wikipedia: http://www.wikipedia.org/

Naturally, many of these terms and their definitions have floated around the Internet for some time, and in most cases it would impossible to locate the original sources. However, I reference the online source (or academic paper) in which I located the term’s definition. • If the term definition is taken directly from an existing source, I reference it as (Source: [name of source]). 229

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• If the core definition is taken from an existing source but I modified it, I state it as such (Source: modified from [name of source]). • In some cases, I have substantially reworked or developed the definition, and in these cases, I provide no source. With each term, I also provide a reference to the appropriate chapter in the book for you to explore the theoretical aspects of the term (i.e., (see Chapter [chapter number] [chapter subject]). A/B Testing: testing two variables for a statistically significant influence. In sponsored search, it is typically the process of randomly showing a visitor one version of an ad or landing page (i.e., version A and version B) and tracking differences in behavior for each version. Version A is normally the baseline control design and version B is the independent design. A/B tests are commonly applied to clicked-on ad copy and landing page copy or designs to determine which version drives the more desired result. A/B testing is a method that has been commonly used for years in direct marketing and adopted within the interactive space (Source: modified from Quirk, SEMPO, and WebTrends) (see Chapter 7 analytics). Abandonment: when a visitor exits or leaves a conversion process on an ad or landing page (Source: modified from WebTrends) (see Chapter 5 customers). Abort: when a Web server does not successfully transfer a unit of content or ad to a browser. This is usually caused by a user hitting the stop button or clicking on another link prior to the completion of a download (Source: IAB) (see Chapter 5 consumers). Above the fold: the section of a Web page that is visible on a screen without scrolling. It comes from the newspaper industry, referring to the top fold of the newspaper (Source: modified from SearchEngineDictionary.com and Marketing Terms.com) (see Chapter 4 ads). Accuracy: the ability of a measurement to match the actual value of the quantity being measured. In statistical terms, accuracy is the width of the confidence interval for a desired confidence level. Accuracy is the foundation on which your marketing analytics should be built (Source: modified from WebTrends) (see Chapter 7 analytics). Acquisition cost: total cost of an advertising/marketing campaign divided by the number of visitors (this is visitor acquisition cost) or divided by the number of customers (this is customer acquisition cost); an important metric in effective PPC advertising (Source: modified from SearchEngineDictionary.com) (see Chapter 5 consumers). Acquisition: the point at which a visitor becomes a qualified lead/customer. Generally this is the point where the visitor buys a product or provides contact details and indicates an interest in the product or service. Also refers to the process of gaining customers through the means of different marketing strategies (Source: modified from WebTrends and SearchEngineDictionary.com) (see Chapter 7 analytics). Action: a specified task performed by a user (Source: modified from Quirk) (see Chapter 7 analytics). Actionable data: information that allows one to make a decision (Source: modified from WebTrends) (see Chapter 7 analytics).

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Active Verb: an action word, usually used in a call to action (CTA) that tells a visitor what to do (Source: Quirk) (see Chapter 4 ads). Activity audit: independent verification of measured activity for a specified time period. Some of the key metrics validated are ad impressions, page impressions, clicks, total visits, and unique users. An activity audit results in a report verifying the metrics (Source: IAB) (see Chapter 7 analytics). Ad audience: the number of unique users exposed to an ad within a specified time period (Source: IAB) (see Chapter 7 analytics). Ad banner: a graphic image or other media object used as an advertisement (Source: IAB) (see Chapter 4 ads). Ad blocker: software on a user’s browser that prevents advertisements from being displayed (Source: IAB) (see Chapter 5 consumers). Ad blocking: the blocking of Web advertisements, typically the image in graphical Web advertisements (Source: Marketing Terms.com) (see Chapter 5 consumers). Ad broker: an Internet advertising specialist. Ad brokers act as middlemen between Web site owners with advertising space to sell and advertisers (Source: SearchEngineDictionary.com) (see Chapter 2 model). Ad campaign audit: an activity audit for a specific ad campaign (Source: IAB) (see Chapter 7 analytics). Ad centric measurement: audience measurement derived from a third-party ad server’s own server logs (Source: IAB) (see Chapter 7 analytics). Ad click: a click on an advertisement on a Web page, which takes a user to another site (Source: modified from WebTrends) (see Chapter 7 analytics). Ad copy: the main text of a clickable search or context-served ad. It usually makes up the second and third lines of a displayed ad, between the Ad Title and the Display URL (Source: SEMPO) (see Chapter 4 ads). Ad display / Ad delivered: when an ad is successfully displayed on the user’s computer screen (Source: IAB) (see Chapter 7 analytics). Ad download: when an ad is downloaded by a server to a user’s browser. Ads can be requested, but aborted or abandoned before actually being downloaded to the browser, and hence there would be no opportunity to see the ad by the user (Source: IAB) (see Chapter 7 analytics). Ad impression: can have multiple meanings depending on the context (Source: IAB) (see Chapter 7 analytics): • An ad served to a user’s browser. Ads can be requested by the user’s browser. • The measurement of responses from an ad delivery system to an ad request from the user’s browser, which is filtered from robotic activity and is recorded at a point as late as possible in the process of delivery of the creative material to the user’s browser€– therefore closest to the actual opportunity to be seen by the user. • Ad impression ratio: click-throughs divided by ad impressions. It is more commonly known as the click-through rate (CTR) (Source: IAB) (see Chapter 7 analytics):

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Ad insertion: when an ad is inserted in a document and recorded by the ad server (Source: IAB) (see Chapter 2 model). Ad inventory: the number of potential page views a site has available for advertising (Source: SearchEngineDictionary.com) (see Chapter 3 model). Ad materials: the creative artwork, copy, active URLs, and active target sites due to the seller prior to the initiation of the ad campaign (Source: IAB) (see Chapter 4 ads). Ad network: an aggregator or broker of advertising inventory for many sites. Ad networks are the sales representatives for the Web sites within the network (Source: IAB) (see Chapter 2 model). Ad recall: a measure of advertising effectiveness in which a sample of respondents is exposed to an ad and then at a later point in time is asked if they remember the ad. Ad recall can be on an aided or unaided basis. Aided ad recall is when the respondent is told the name of the brand or category being advertised (Source: IAB) (see Chapter 7 analytics). Ad request: the request for an advertisement as a direct result of a user’s action as recorded by the ad server. Ad requests can come directly from the user’s browser or from an intermediate Internet resource, such as a Web content server (Source: IAB) (see Chapter 7 analytics). Ad serving: the delivery of ads by a server to an end-user’s computer on which the ads are then (Source: IAB) (see Chapter 2 model). Ad space: the allocated real estate on a Web page of a site in which an advertisement can be placed. Each space on a site is uniquely identified. Multiple ad spaces can exist on a single page (Source: modified from IAB, Marketing Terms.com, and Quick) (see Chapter 2 model). Ad stream: the series of ads displayed by the user during a single visit to a site (also impression stream) (Source: IAB) (see Chapter 7 analytics). Ad title: the first line of text displayed in a clickable search or context-served ad. Ad titles serve as ad headlines (Source: SEMPO) (see Chapter 4 ads). Ad transfers: the successful display of an advertiser’s Web site after the user clicked on an ad. When a user clicks on an advertisement, a click-through is recorded and redirects or “transfers” the user’s browser to an advertiser’s Web site. If the user successfully displays the advertiser’s Web site, an ad transfer is recorded (Source: IAB) (see Chapter 7 analytics). Ad view: when the ad is actually seen by the user. Note this is not measurable today. The best approximation today is provided by ad displays, when a Web page displays an ad (Source: modified from IAB and WebTrends) (see Chapter 7 analytics). Ad (or Advertisement): the commercial portion of message content for which an advertiser has or will pay when a searcher sees their content after submitting a query in a search engine or Web site search box, which will typically take a searcher to another Web page (Source: modified from SEMPO, IAB, and WebTrends) (see Chapter 4 ads). Address: a unique identifier for a computer or site online, usually a URL for a Web site or marked with an @ for an e-mail address. Literally, it is how one

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computer finds the location of another computer using the Internet (Source: IAB) (see Chapter 2 model). Adjacency: referring to the relationship between words, particularly words used in a search engine query. Search engines typically assign higher value to pages where the search terms appear next to one another (as in the query) than to pages where the search terms are separated by other words (Source: SearchEngineDictionary.com) (see Chapter 4 ads) Advertiser: the company paying for the advertisement (Source: IAB) (see Chapter 2 model). Advertising agency: a service business dedicated to creating, planning, and handling advertising (and sometimes other forms of promotion) for its clients. An ad agency is independent from the client and provides an outside point of view to the effort of selling the client’s products or services. An agency can also handle overall marketing, branding strategies, and sales promotions for its clients (Source: Wikipedia) (see Chapter 6 BAM!). Advertising blockade: where one advertiser purchases all advertising outlets at a given point in time or space (see Chapter 4 ads). Advertising frequency: how often an advertisement is shown (see Chapter 7 analytics). Advertising network: a service allowing advertising buyers to reach broad audiences relatively easily through run-of-category and run-of-network buys where ads are bought centrally through one company and displayed on multiple Web sites that contract with that company for a share of revenue generated by ads served on their site (Source: modified from Search Engine Watch and Marketing Terms.com) (see Chapter 2 model). Advertising reach: refers to the total number of different people or households exposed, at least once, to a medium during a given period of time. (Source: Wikipedia) (see Chapter 6 BAM!). Adware: advertiser-supported software; typically downloaded with other applications such as peer-to-peer file sharing. (Source: Advertising.com) (see Chapter 2 model). Affiliate marketing: process of revenue sharing where merchants duplicate sales efforts by enlisting other Web sites as a type of outside sales force. In return, the affiliate receives a percentage of sales or some other form of compensation generated by that traffic. Successful affiliate marketing programs result in the merchant attracting additional buyers, and the affiliate earning the equivalent of a referral fee, based on click-through referrals to the merchant site (Source: modified from SEMPO and Quick) (see Chapter 2 model). Affinity marketing: selling products or services to customers on the basis of their established buying patterns (Source: IAB) (see Chapter 2 model). Algorithms: sets of rules to solve a problem or some end, typically via the use of some programming language (see Chapter 2 model). Alternate text: a word or phrase displayed when a user has image loading disabled in their browser or when a user abandons a page by hitting “stop” in their browser

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prior to the transfer of all images. Also appears as balloon text when a user lets their mouse rest over an image (Source: IAB) (see Chapter 4 ads). Anchor text: the clickable text part of a hyperlink. The text usually gives visitors or search engines important information on what the page being linked to is about (Source: Search Engine Watch) (see Chapter 2 model). Anonymizer: an intermediary that prevents Web sites from seeing a user’s Internet Protocol (IP) address (Source: IAB) (see Chapter 2 model). Average Order Value (AOV): amount of revenue generated by an order from a customer (see Chapter 7 analytics). Applet: a small, self-contained software application that is most often used by browsers to automatically display animation and / or to perform database queries requested by the user (Source: IAB) (see Chapter 2 model). Applicable browser: any browser an ad will impact, regardless of whether it will play the ad (Source: IAB) (see Chapter 2 model). ATL (above the line) promotions: are tailored for a mass audience. ATL promotions can establish brand identity, but they are also difficult to measure well (Source: Wikipedia) (see Chapter 4 ads). Attitude: is a predisposition or a tendency to respond positively or negatively to a certain idea, object, person, or situation. Attitude influences an individual’s choice of action and responses to challenges, incentives, and rewards (together called stimuli). Four major components of attitude are (Source: BusinessDictionary) (see Chapter 5 consumer): • Affective: emotions or feelings • Cognitive: belief or opinions held consciously • Evaluative: positive or negative response to stimuli. Attrition: the erosion of a customer base over time. It is the opposite of customer retention (Source: WebTrends) (see Chapter 5 consumer). Auction model bidding: is the most popular type of pay-per-click (PPC) bidding. First, an advertiser determines what maximum amount per click they are willing to spend for a keyword. If there is no competition for that keyword, the advertiser pays their bid, or less, for every click. If there is competition at auction for that keyword, then the advertiser with the highest bid will pay one penny more than their nearest competitor. For example, advertiser A is willing to bid up to $0.50; advertiser B is willing to bid up to $0.75. If advertiser A’s actual bid is $0.23, then advertiser B will only pay $0.24 per click. It is also referred to as market or competition-driven bidding (Source: SEMPO) (see Chapter 8 auctions). Audience reach: in the context of search engines, the term refers to the percentage of the total Internet population that uses a particular search engine during a given month. Together with search hours, audience reach is an important measure when calculating the popularity of the different search engines (Source: SearchEngineDictionary. com) (see Chapter 6 BAM! and Chapter 7 analytics).

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Audit: third-party validation of log activity and/or measurement process associated with Internet activity/advertising. Activity audits validate measurement counts. Process audits validate internal controls associated with measurement (Source: IAB) (see Chapter 7 analytics). Auditor: a third-party independent organization that performs audits (Source: IAB) (see Chapter 7 analytics). Banner ad: an advertisement embedded on a Web page usually intended to drive traffic to a different Web site by linking to the advertiser’s site. The Interactive Advertising Bureau (IAB) has created a standard set of banner ad sizes (Medium Rectangle, Rectangle, Leaderboard, Wide Skyscraper) into a set of guidelines called the Universal Ad Package (Source: WebTrends) (see Chapter 4 ads). Banner blindness: refers to a “condition” among experienced Web users who tend to automatically ignore banner ads, even when the banner ads contain information visitors are actively looking for. Banner blindness is arguably the main cause of low clickthrough rates in banner advertising (Source: modified from SearchEngineDictionary. com and Marketing Terms.com) (see Chapter 5 customers). Barter: the exchange of goods and services without the use of cash. The value of the barter is the dollar value of the goods and services being exchanged for advertising. This is a recognized form of revenue under the Generally Accepted Accounting Principles (GAAP) (Source: IAB) (see Chapter 8 auctions). Behavioral targeting: the practice of targeting and serving ads to groups of people who exhibit similarities not only in their location, gender, or age, but also in how they act and react in their online environment, with the goal of increasing the effectiveness of their campaigns. Behaviors tracked and targeted include Web site topic areas they frequently visit or subscribe to, subjects or content or shopping categories for which they have registered, profiled themselves, or requested automatic updates and information, and so on (Source: modified from SEMPO and IAB) (see Chapter 5 customers). Beta: a test version of a product, such as a Web site, software, or ad prior to final release (Source: IAB) (see Chapter 2 ads). Bias: inclination or preference that influences (but ought not to) one’s judgment from being balanced or even-handed. Prejudice is bias in pejorative sense (Source: Business Dictionary) (see Chapter 5 customers). Bid: the maximum amount of money that an advertiser is willing to pay each time a searcher clicks on an ad. Bid prices can vary widely depending on competition from other advertisers and keyword popularity (Source: SEMPO) (see Chapter 8 auctions). Bid boosting: a form of automated bid management that allows you to increase your bids when ads are served to someone whose age or gender matches your target market (Source: modified from SEMPO) (see Chapter 8 auctions). Bid management software: software that manages PPC campaigns automatically, called either rules-based (with triggering rules or conditions set by the advertiser) or intelligent software (enacting real-time adjustments based on tracked conversions and competitor actions). Both types of automatic bid management programs monitor

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and change bid prices, pause campaigns, manage budget maximums, and adjust multiple keyword bids based on CTR, position ranking, and more (Source: SEMPO) (see Chapter 8 auctions). Bonus impressions: additional ad impressions above the commitments outlined in the approved insertion order (Source: IAB) (see Chapter 2 model). Bot: software that runs automatically without human intervention. Typically, a bot is endowed with the capability to react to different situations it may encounter. Two common types of bots are agents and spiders. Bots are used by companies like search engines to discover Web sites for indexing. Short for robot (Source: IAB) (see Chapter 2 model). Bounce: a visitor whose behaviors are classified within the bounce rate (see Chapter 7 analytics). Bounce rate: refers to the percentage of people that immediately exit or do not progress beyond the entry page within a certain time limit (Source: modified from Quirk and WebTrends) (see Chapter 7 analytics). Brand: distinctive name or trademark that identifies a product or manufacturer. A symbol (name, logo, symbols, fonts, colors), a slogan, and a design scheme representing a company. Brand is often developed to represent implicit values, ideas, and even personality (Source: modified from Quirk and SEMPO) (see Chapter 6 BAM!). Brand awareness: a measure of how quickly a brand is recognized or called to mind (Source: Quirk) (see Chapter 6 BAM!). Brand evangelist: one who lives and breathes a brand, and is capable of spreading the word far and wide (Source: Quirk) (see Chapter 6 BAM!). Brand lift: a measurable increase in consumer recall for a specific, branded company, product, or service. For example, brand lift might show an increase in respondents who think of Dell for computers, or Wal-Mart for “every household thing” (Source: SEMPO) (see Chapter 6 BAM!). Brand messaging: creative messaging that presents and maintains a consistent corporate image across all media channels, including search (Source: SEMPO) (see Chapter 6 BAM!). Brand reputation: the position a company brand occupies (Source: SEMPO) (see Chapter 6 BAM!). Brand terrorist: one who attacks a brand, normally an industry rival or dissatisfied customer (Source: Quirk) (see Chapter 6 BAM!). Branding: a brand is a customer experience represented by a collection of images and ideas; often, it refers to a symbol such as a name, logo, slogan, and design scheme. Brand recognition and other reactions are created by the accumulation of experiences with the specific product or service, both directly relating to its use, and through the influence of advertising, design, and media commentary. A brand often includes an explicit logo, fonts, color schemes, symbols, and sound that may be developed to represent implicit values, ideas, and even personality (Source: modified from SEMPO) (see Chapter 6 BAM!).

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Branding strategy: is the attempt to develop a strong brand reputation on the Web to increase brand recognition and create a significant volume of impressions (Source: SEMPO) (see Chapter 6 BAM!). Browser: has a couple of meanings depending on the context (Source: IAB) (see Chapter 2 model): • The visitor views more pages on your Web site after the landing page. • A software program that can request, download, cache, and display documents available on the World Wide Web. BTL (below the line) promotions: are targeted at individuals according to their needs or preferences. BTL can actually lead to a sale, and BTL promotions are highly measurable, giving marketers valuable insights into their return on investment (ROI) (Source: Wikipedia) (see Chapter BAM!). BtoB/B2B (Business-to-Business): businesses whose primary customers are other businesses (Source: IAB) (see Chapter 6 BAM!). BtoC/B2C (Business-to-Consumer): businesses whose primary customers are consumers (Source: IAB) (see Chapter 6 BAM!). Business intelligence: business practices that foster customer care, loyalty, and/or customer support. Also refers to a category of software and tools designed to gather, store, analyze, and deliver data in a user-friendly format to help organizations make more informed business decisions (Source: modified from WebTrends and IAB) (see Chapter 6 BAM!). Button: can have a couple of meanings depending on the context (Source: IAB) (see Chapter 2 model): • clickable graphic that contains certain functionality, such as taking one someplace or executing a program • buttons can also be ads. See iab.net for voluntary guidelines defining specifications of button ads. Buying funnel: refers to a multistep process of a consumer’s path to purchase a product: from awareness, to education, to preferences and intent, to final purchase. Also called the Buying Cycle, Buyer Decision Cycle, and Sales Cycle (Source: SEMPO) (see Chapter 5 customer). Buzz: online excitement and word of mouth surrounding a certain brand or incident (Source: Quirk) (see Chapter 6 BAM!). Caching: the storage of Web files for later reuse at a point more quickly accessed by the end-user. (Source: Marketing Terms.com) (see Chapter 2 model). Call to Action (CTA): a phrase written to motivate the reader to take a specific action and is usually situated at the bottom of a page. These actions can include signing up for a newsletter, contacting the company, or booking a holiday (Source: Quirk) (see Chapter 4 ads).

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Campaign analysis: a feature that tracks activity originating from a marketing campaign, so you can compare your campaigns and evaluate their effectiveness. Campaigns are tracked using a query parameter on the marketing campaign landing page (Source: WebTrends) (see Chapter 7 analytics). Campaign integration: planning and executing a paid search campaign concurrently with other marketing initiatives, online, offline, or both. More than simply launching simultaneous campaigns, true paid search integration takes all marketing initiatives into consideration prior to launch, such as consistent messaging and image, driving offline conversions, supporting brand awareness, increasing response rates, and contributing to ROI business goals (Source: SEMPO) (see Chapter 7 analytics). Campaign strategist: the person who is responsible for making the objectives of a campaign a reality, by any means necessary (Source: modified from Quirk) (see Chapter 7 analytics). Cannibalism: in marketing, situation where the sales of a new (introduced as an extension of an established brand) or differently branded product eat into the sales of other products within the same line. If the total sales revenue of that product line increases, then the line extension is justifiable. However the danger of weakening the main brand remains (Source: BusinessDictionary) (see Chapter 6 BAM!). Cascading style sheets (CSS): a data format used to separate style from structure on Web pages (Source: Marketing Terms.com) (see Chapter 2 model). Channel: (1) a band of similar content; (2) a type of sales outlet (also known as channel of distribution), for example retail, catalog, or e-commerce. (Source: IAB) (see Chapter 6 BAM!). Click: the visitor sees your ad and clicks it (see Chapter 7 analytics). Click bot: a program generally used to artificially click on paid listings within the engines in order to artificially inflate click amounts. (Source: SEMPO) (see Chapter 2 model). Click fraud: the act of generating invalid clicks on an ad that occurs in pay-per-click online advertising when a person, automated script, or computer program imitates a legitimate user of a Web browser clicking on an ad, for the purpose of generating a charge per click without having actual interest in the target of the ad’s link (Source: modified from WebTrends and Quick) (see Chapter 7 analytics). Click paths: the pattern of clicks as well as the entry and exit points of a user’s interaction with a Web site (Source: Quirk) (see Chapter 7 analytics). Click potential: the expected percent change in click-throughs in relation to rank 1. This factor represents the combined impact of changes in impressions and clickthrough rate by rank (see Chapter 7 analytics). Click tracking: using scripts to track the number of clicks it takes to enter or exit a Web site. This can also be used to shield a link from being picked up as a back link to another site (Source: Quirk) (see Chapter 7 analytics). Clicks and mortar: a business that has both online trading capabilities and physical stores located offline (Source: Quirk) (see Chapter 2 model).

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Clicks: (1) metric that measures the reaction of a user to an Internet ad. There are three types of clicks: click-throughs; in-unit clicks; and mouseovers; (2) the opportunity for a user to download another file by clicking on an advertisement, as recorded by the server; (3) the result of a measurable interaction with an advertisement or keyword that links to the advertiser’s intended Web site or another page or frame within the Web site; (4) metric that measures the reaction of a user to linked editorial content. See iab.net for ad campaign measurement guidelines (Source: IAB) (see Chapter 7 analytics). Click-stream: (1) the electronic path a user takes while navigating from site to site, and from page to page within a site; (2) a comprehensive body of data describing the sequence of activity between a user’s browser and any other Internet resource, such as a Web site or third-party ad server (Source: IAB) (see Chapter 7 analytics). Click-through: the action of following a link within an advertisement or editorial content to another Web site or another page or frame within the Web site. Reported as a 302 redirect at the ad server and should filter out robotic activity (Source: IAB) (see Chapter 7 analytics). Click-through lift: the increase in CTR resulting from a change (see Chapter 7 analytics). Click-through rate (CTR): the rate (expressed in a percentage) at which users click on an ad. This is calculated by dividing the total number of clicks by the total number of ad impressions. CTR is an important metric for Internet marketers to measure the performance of an ad campaign (Source: Search Engine Watch) (see Chapter 7 analytics). Click-within: similar to click down or click. More commonly, however, clickwithins are ads that allow the user to drill down and click while remaining in the advertisement, not leaving the site on which they are residing (Source: IAB) (see Chapter 7 analytics). Client: A computer or software program that contacts a server to obtain data via the Internet or another network. Internet Explorer, Outlook, and other browsers and e-mail programs are examples of software clients (Source: IAB) (see Chapter 2 model). Client-initiated ad impression: one of the two methods used for ad counting. Ad content is delivered to the user via two methods: server-initiated and client-initiated. Client-initiated ad counting relies on the user’s browser for making requests and formatting and redirecting content. For organizations using a client-initiated ad counting method, counting should occur at the publisher’s ad server or third-party ad server, subsequent to the ad request or later in the process. See server-initiated ad impression (Source: IAB) (see Chapter 7 analytics). Client-side: transactions that take place before information is sent to the server (Source: Quirk) (see Chapter 2 model). Client-side tracking: client-side tracking entails the process of tagging every page that requires tracking on the Web site with a block of JavaScript code. This method is cookie-based (available as first- or third-party cookies) and is readily available to companies who do not own or manage their own servers (Source: SEMPO) (see Chapter 7 analytics).

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Close: indicates that the user clicks or otherwise activates a close control that fully dispatches the ad from the player environment. May not apply to nonoverlay ads (Source: IAB) (see Chapter 7 analytics). Competitive: to have good enough value to compete against commercial rivals (Source: Quirk) (see Chapter 6 BAM!). Competitive analysis: as used in SEO, CA is the assessment and analysis of strengths and weaknesses of competing Web sites, including identifying traffic patterns, major traffic sources, and keyword selection (Source: SEMPO) (see Chapter 6 BAM!). Concept search: a search for documents related conceptually to a search term, rather than for documents that actually contain the search term itself (Source: SearchEngineDictionary.com) (see Chapter 3 keywords). Consumer: is a broad label for any individuals or households that use goods and services generated within the economy (see Chapter 5 customers). Consumer packaged goods (CPG): typically consumable goods, including food and beverages, footwear and apparel, tobacco, and cleaning (see Chapter BAM!). Content integration: advertising woven into editorial content or placed in a contextual envelope. Also known as “Web advertorial” (Source: IAB) (see Chapter 6 BAM!). Content network: networks that serve paid search ads triggered by keywords related to the page content a user is viewing, in exchange for a share of the revenue generated by those ads. For example: Google AdSense or the Yahoo Publisher Network (Source: modified from Search Engine Watch and SEMPO) (see Chapter 2 model). Content targeting: an ad-serving process in Google and Yahoo! that displays keyword triggered ads related to the content or subject (context) of the Web site a user is viewing. Contrast to search network servers, in which an ad is displayed when a user types a keyword into the search box of a search engine or one of its partner sites (Source: SEMPO) (see Chapter 2 model). Contextual ads: existing contextual ad engines deliver text and image ads to nonsearch content pages. Ads are matched to keywords extracted from content. Advertisers can leverage existing keyboard-based paid search campaigns and gain access to a larger audience (Source: IAB) (see Chapter 4 ads). Contextual advertising: advertising that is automatically served or placed on a Web page based on the page’s content, keywords, and phrases rather than on based on a query (Source: modified from SEMPO and Quirk) (see Chapter 4 ads). Contextual distribution: the marketing decision to display search ads on certain publisher sites across the Web instead of, or in addition to, placing PPC ads on search networks (Source: SEMPO) (see Chapter 2 model). Contextual link ads/inventory: to supplement their business models, certain textlink advertising networks (like Google) have expanded their network distribution to include “contextual inventory.” Most vendors of “search engine traffic” have expanded the definition of Search Engine Marketing to include this contextual inventory. Contextual or content inventory is generated when listings are displayed on pages of Web sites (usually not search engines) where the written content on the

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page indicates to the ad server that the page is a good match to specific keywords and phrases. Often this matching method is validated by measuring the number of times a viewer clicks on the displayed ad. These ads typically do not perform as well as traditional text ads on search engines, but the lower cost justifies the expense (Source: WebTrends) (see Chapter 2 BAM!). Contextual search campaigns: a paid placement search campaign that takes a search ad listing beyond search engine results pages and onto the sites of matched content Web partners (Source: SEMPO) (see Chapter 2 model). Contextual search: a search that analyzes the page being viewed by a user and gives a list of related search results (Source: SEMPO) (see Chapter 2 model). Conversion: to describe the primary measurable events, advertisers use to gauge the effectiveness of their advertising campaigns. An action that signifies a completion of a specified activity. For many sites, a user converts if they buy a product, sign up for a newsletter, or download a file. The conversion rate is the percentage of visitors who do convert. Cookie deletion can have an impact on your conversion rate because if a cookie is being systematically deleted, repeat visitor rates will be undercounted and new visitor rates will be overcounted, thus skewing the conversion rate metric by which you analyze your site’s overall effectiveness (Source: modified from WebTrends) (see Chapter 7 analytics). Conversion action: the desired action you want a visitor to take on your site. Includes purchase, subscription to the company newsletter, request for follow-up or more information (lead generation), download of a company free offer (research results, a video, or a tool), and subscription to company updates and news (Source: SEMPO) (see Chapter 7 analytics). Conversion cost: total cost-per-sale, calculated by dividing the total cost of an advertising campaign by the number of resulting sales. For example, if $1,000 is spent on an advertising campaign and that campaign results in 20 sales, the conversion costper-sale is $50 ($1,000 / 20). That means it costs $50 to generate one sale (Source: SearchEngineDictionary.com) (see Chapter 7 analytics). Conversion funnel: the series of steps that move a visitor toward a specified conversion event, such as an order or registration signup. Related to the buying funnel (Source: modified from WebTrends) (see Chapter 5 customer). Conversion point: conversion points are the points at which your customers have completed a specific action on your Web site. Common conversion points are: Newsletter sign up: the “thank you for subscribing” page, Order/Sale: the “thank you for your order” page, Download: the “Your download is complete” page (Source: SearchEngineDictionary.com) (see Chapter 7 analytics). Conversion potential: the expected percent change in conversions in relation to rank 1. This factor combines the effects of traffic volume and changes in conversion rates by rank (see Chapter 7 analytics). Conversion rate: the percentage of site visitors that deliver the most wanted response (MWR). The number of visitors who convert (take a desired action at your site) after

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clicking through on your ad, divided by the total number of click-throughs to your site for that ad. Conversion rates are measurements that determine how many of your prospects perform the prescribed or desired action step (Source: modified from SEMPO and SearchEngineDictionary.com) (see Chapter 7 analytics). Cookie: information stored on a user’s computer via a browser by a Web site for the purpose of identifying that browser during audience activity and between visits or sessions (Source: modified from Marketing Terms.com and IAB) (see Chapter 2 model). Cookie buster: software that blocks the placement of cookies on a user’s browser (Source: IAB) (see Chapter 2 model). Copy testing: a specialized field of marketing research. It is the study of television commercials prior to airing them and is defined as research to determine an ad’s effectiveness based on consumers’ responses to the ad. It covers all media including print, TV, radio, the Internet, and so on (see Chapter 4 ads). Cost: valuation in terms of money of (1) effort, (2) material, (3) resources, (4) time and utilities consumed, (5) risks incurred, and (6) opportunity forgone in production and delivery of a good or service. All expenses are costs, but not all costs (such as those incurred in acquisition of an income-generating asset) are expenses (Source: BusinessDictionary) (see Chapter 6 BAM!). Cost of acquisition (COA): how much it costs to acquire a conversion (desired action), such as a sale (Source: SEMPO) (see Chapter 7 analytics). Cost per action (CPA): a form of advertising where payment is dependent on an action that a user performs as a result of the ad. The action could be making a purchase, signing up for a newsletter, or asking for a follow-up call. An advertiser pays a set fee to the publisher based on the number of visitors who take action. Many affiliate programs use the CPA model (Source: Search Engine Watch) (see Chapter 7 analytics). Cost per click (CPC): the cost or cost-equivalent pay per click-through. Also called Pay per Click (PPC). A performance-based advertising model where the advertiser pays a set fee for every click on an ad. The majority of text ads sold by search engines are billed under the CPC model (Source: modified from Search Engine Watch and Marketing Terms.com) (see Chapter 7 analytics). Cost-per-Customer: the cost an advertiser pays to acquire a customer (Source: IAB) (see Chapter 7 analytics). Cost-per-lead (CPL): cost of advertising based on the number of database files (leads) received (Source: IAB) (see Chapter 7 analytics). Cost per order (CPO): the dollar amount of advertising or marketing necessary to acquire an order. Calculated by dividing marketing expenses by the number of orders. Also referred to as CPA (Cost per Acquisition) (Source: modified from SEMPO) (see Chapter 7 analytics). Cost-per-sale (CPS): the advertiser’s cost to generate one sales transaction. If this is being used in conjunction with a media buy, a cookie can be offered on the content site and read on the advertiser’s site after the successful completion of an online sale (Source: IAB) (see Chapter 7 analytics).

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Cost per targeted thousand impressions (CPTM): implying that the audience one is trying to reach is defined by particular demographics or other specific characteristics, such as male golfers age 18–25. The difference between CPM and CPTM is that CPM is for gross impressions whereas CPTM is for targeted impressions (Source: IAB) (see Chapter 7 analytics). Cost per thousand (CPM): an ad model that charges advertisers every time an ad is displayed to a user, whether the user clicks on the ad or not. The fee is based on every 1,000 ad impressions (M is the Roman numeral for 1,000). Most display ads, such as banner ads, are sold by CPM. This term is heavily used in print, broadcasting, and direct marketing (Source: modified from Search Engine Watch and WebTrends) (see Chapter 7 analytics). Cost-per-transaction (CPT): the dollar amount of advertising or marketing necessary to acquire an order. Calculated by dividing marketing expenses by the number of orders. Also referred to as CPA (Cost per Acquisition) (Source: modified from SEMPO) (see Chapter 7 analytics). Count: raw figures captured for analysis. These are the most basic Web analytics metric (Source: Quirk) (see Chapter 7 analytics). Count audit: see activity audit (Source: IAB) (see Chapter 7 analytics). Crawler: a software program that visits Web pages to build indexes for search engines. See also spider, bot, and intelligent agent (Source: IAB) (see Chapter 2 model). Creative: for the purposes of Web analytics, “creative” describes the characteristics of a marketing activity, such as color, size, and messaging€– for example, a “Buy Now” graphic (Source: WebTrends) (see Chapter 4 ads). Creatives: unique words, design, and display of a paid-space advertisement. In paid search advertising, creative refers to the ad’s title (headline), description (text offer), and display URL (clickable link to advertiser’s Web site landing page). Unique creative display includes word emphasis (boldfaced, italicized, in quotes), typeface style, and, on some sites, added graphic images, logos, animation, or video clips (Source: SEMPO) (see Chapter 4 ads). Cross marketing: marketing other products or services to an existing customer. Cross marketing enhances the ability of generating further sales. Also known as Cross Selling (Source: Quirk) (see Chapter 6 BAM!). Cross selling: selling an additional product or service to an existing customer (see Chapter 6 BAM!). Crowd sourcing: taking a task that would conventionally be performed by a contractor or employee and turning it over to a typically large, undefined group of people via an open call for responses (Source: IAB) (see Chapter 6 BAM!). Customer: a person who buys or uses goods or services. A person with whom a business must deal (Source: Quirk) (see Chapter 5 customers). Customer acquisition cost: the cost associated with acquiring a new customer (Source: Marketing Terms.com) (see Chapter 7 analytics).

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Customer life cycle: the progressive steps a customer goes through when purchasing, using, or considering a product or service (Source: Quirk) (see Chapter 6 BAM!). Customer segment: a powerful aspect of relationship marketing in which you target a subsection or group of customers who share a specific trait or set of behaviors. See also demographics and psychographics (Source: WebTrends) (see Chapter BAM!). Data: information that has been translated into a form that is more convenient to move or process (see Chapter 7 analytics). Dayparting: the ability to specify different times of day, or day of week, for ad displays as a way to target searchers more specifically. An option that limits serves of specified ads based on day and time factors (Source: SEMPO) (see Chapter BAM!). Demographics: common characteristics used for population or audience segmentation, such as age, gender, household income, and the like. The physical characteristics of human populations and segments of populations often used to identify consumer markets. Demographics can include information such as age, gender, marital status, education, and geographic location. See also psychographics (Source: modified from WebTrends and IAB) (see Chapter 6 BAM!). Description: in the context of the search engines, the description refers to the descriptive text accompanied by a title and URL in the search results page. Some search engines take this description from the meta description whereas most generate their own from the page content. Directories often ask for a description when you submit your page (Source: SearchEngineDictionary.com) (see Chapter 4 ads). DIKW: Data, Information, Knowledge, and Wisdom, a hierarchy of understanding this overloaded term€– information (see Chapter 7 analytics). Display advertising: a form of online advertising where an advertiser’s message is shown on a destination Web page, generally set off in a box at the top or bottom or to one side of the content of the page (Source: IAB) (see Chapter BAM!). Display URL: the Web page URL that one actually sees in a PPC text ad. Display URL usually appears as the last line in the ad; it may be a simplified path for the longer actual URL, which is not visible (Source: SEMPO) (see Chapter 4 ads). Distribution network: a network of Web sites (content publishers, ISPs) or search engines and their partner sites on which paid ads can be distributed. The network receives advertisements from the host search engine, paid for with a CPC or CPM model (Source: SEMPO) (see Chapter 6 BAM!). DIY: Do It Yourself (see Chapter 2 model). Drop shipper: a company that fulfills the order for another seller (see Chapter 6 BAM!). Dynamic ad insertion: the process by which an ad is inserted into a page in response to a user’s request. Dynamic ad placement allows alteration of specific ads placed on a page based on any data available to the placement program. At its simplest, dynamic ad placement allows for multiple ads to be rotated through one or more spaces. In

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more sophisticated examples, the ad placement could be affected by demographic data or usage history for the current user (Source: IAB) (see Chapter 2 model). Dynamic ad placement: process by which an ad is inserted into a page in response to a user’s request; dynamic ad placement allows alteration of specific ads placed on a page based on any data available to the placement program (Source: IAB) (see Chapter 2 model). Dynamic content: Web site content generated automatically, usually from a database and based on user actions/selections. Dynamic content typically changes at regular intervals, for example, daily or each time the users reload the page. SERPs are dynamically generated pages, changing depending on user input (Source: SearchEngineDictionary.com) (see Chapter 2 model). Dynamic IP address: an IP address (assigned by an ISP to a client PC) that changes periodically (Source: IAB) (see Chapter 2 model). Dynamic keyword bidding: process by which keyword bids are varied per term according to user behavior, competitor activity, time of day, day of week, and so on (Source: Advertising.com) (see Chapter 8 auctions). Dynamic keyword insertion: in sponsored search advertising, this allows keywords used in searches to be inserted into advert copy (Source: modified from Quirk) (see Chapter 4 ads). Dynamic rotation: delivery of ads on a rotating, random basis so that users are exposed to different ads and ads are served in different pages of the site (Source: IAB) (see Chapter 2 model). East: the ads on the right side as the searcher is facing the SERP. Also known as the right rail (see Chapter 4 ads). E-commerce: conducting commercial transactions, specifically the process of selling products or services, on the Internet where goods, information, or services are bought and sold (Source: modified from SEMPO and IAB) (see Chapter 6 BAM!). Editorial review process: a review process for potential advertiser listings conducted by search engines, which checks to ensure relevancy and compliance with the engine’s editorial policy. This process could be automated, using a spider to crawl ads, or it could be human editorial ad review. Sometimes it is a combination of both. Not all PPC Search Engines review listings (Source: SEMPO) (see Chapter 4 ads). Effective Cost Per Thousand (eCPM): acronym for a hybrid Cost-Per-Click (CPC) auction calculated by multiplying the CPC by the click-through rate (CTR), and multiplying that by one thousand. (Represented by: (CPC x CTR) x 1000 = eCPM.) This monetization model is used by Google to rank site-targeted CPM ads (in the Google content network) against keyword-targeted CPC ads (Google AdWords PPC) in their hybrid auction (Source: SEMPO) (see Chapter 7 analytics). Electronic payment: issuance and receipt of payment via the Internet (Source: Quirk) (see Chapter 2 model). eMarketing: the process of marketing a brand using the Internet (Source: Quirk) (see Chapter 6 BAM!).

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eMarketing strategist: together with the Marketing Managers, the eMarketing Strategists know where and how to effectively position a brand online (Source: Quirk) (see Chapter 6 BAM!). Entry page: refers to any page within a Web site that a user employs to “enter” the Web site. Also see Landing Page (Source: SEMPO) (see Chapter 2 model). Exact match: if not for partial matching, fuzzy matching, collaborative filtering, and stemming, search engines would only return exact matches. A search for “power” would only return documents containing the exact term, not documents containing variations or related terms like powerful and strength (Source: SearchEngineDictionary. com) (see Chapter 3 keywords). Exposure: the showing of an ad to a searcher (see Chapter 4 ads). Eye-tracking studies: studies to track the eye movements of Web page readers in order to understand reading and click-through patterns (Source: modified from SEMPO) (see Chapter 4 ads). Eyeballs: slang term for audience; the number of people who view a certain Web site or advertisement (Source: IAB) (see Chapter 6 BAM!). Fast-moving consumer goods (FMCG): products that are sold quickly at relatively low cost (see Chapter 6 BAM!). First-price auction: an auction in which the bidder who submitted the highest bid is awarded the object being sold and pays a price equal to the amount bid (see Chapter 8 auctions). Fold: an imaginary line across the browser below which a user has to scroll to see content not immediately visible when a Web page loads in a browser. Ads or content displayed above the fold are visible without any end-user interaction. Monitor size and resolution determine where on a Web page the fold lies. All your critical or most important information should lie above the fold to ensure maximum exposure and to entice the user to read more (Source: modified IAB and Quirk) (see Chapter 4 ads). Frequency: the number of occurrences of a repeating event per unit time. The number of times an ad is delivered to the same browser in a single session or time period. A site can use cookies to manage ad frequency. Average frequency is the average of frequencies of all the visitors during the reporting period. Frequency is a retention metric and is part of RFM (recency, frequency, monetary) analysis (Source: modified from IAB and WebTrends) (see Chapter 5 customers). Frequency cap: restriction on the amount of times a specific visitor is shown a particular advertisement. Frequency caps are present to limit the number of times we are exposed to the same online advert (Source: Marketing Terms.com and Quirk) (see Chapter 2 model). Full-service digital agency: an online adverting agency offering products and services in the full range of online marketing (see Chapter 6 BAM!). Geographical targeting: delivery of ads specific to the geographic location of the searcher. Geo-targeting allows the advertiser to specify where ads will or will not be

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shown based on the searcher’s location, enabling more localized and personalized results (Source: Search Engine Watch) (see Chapter 6 BAM!). Goal: the defined action that visitors should perform on a Web site (Source: Quirk) (see Chapter 5 customers). Googlebot: Google uses several user-agents to crawl and index content in the Google.com search engine. Googlebot describes all Google spiders. All Google bots begin with “Googlebot.” For example, Googlebot-Mobile crawls pages for Google’s mobile index, Googlebot-Image crawls pages for Google’s image index (Source: Search Engine Watch) (see Chapter 2 model). Gross exposures: the total number of times an ad is served, including duplicate downloads to the same person (Source: IAB) (see Chapter 2 model). Gross rating points (GRPs): an acronym used in advertising to measure the size of an audience reached by a specific media vehicle or schedule (see Chapter 6 BAM!). Guerilla marketing: unconventional marketing intended to get maximum results from minimal resources (Source: Marketing Terms.com) (see Chapter 6 BAM!). Head terms: search terms that are short, popular, and straightforward (e.g., “helicopter skiing”). These short terms are called “head terms” based on a bell-curve distribution of keyword usage that displays the high numbers of most-used terms at the “head” end of the bell-curve graph (Source: SEMPO) (see Chapter 3 keywords). Heat map: a data visualization tool that shows levels of activity on a Web page in different colors. Reds and yellows show the areas of the most activity and blues and violets the least (Source: Quirk) (see Chapter 4 ads). Heuristic: a way to measure a user’s unique identity. This measure uses deduction or inference based on a rule or algorithm, which is valid for that server. For example, the combination of IP address and user agent can be used to identify a user in some cases. If a server receives a new request from the same client within thirty minutes, it is inferred that a new request comes from the same user and the time since the last page request was spent viewing the last page. Also referred to as an inference (Source: IAB) (see Chapter 7 analytics). Hierarchy of effects: a concept related to the manner in which advertising supposedly works; it is based on the premise that advertising moves individuals systematically through a series of psychological stages such as awareness, interest, desire, conviction, and action (see Chapter 6 BAM!). Hit: the request or retrieval of any item located within a Web page. For example, if a user enters a Web page with five pictures on it, it would be counted as six “hits.” One hit is counted for the Web page itself and another five hits count for the pictures. Webmasters use hits to measure their servers’ workload. Because page designs and visit patterns vary from site to site, the number of hits bears no relationship to the number of pages downloaded, and is therefore a poor guide for traffic measurement (Source: modified from SEMPO and IAB) (see Chapter 7 analytics). Home page: the page designated as the main point of entry of a Web site (or main page) or the starting point when a browser first connects to the Internet. Typically, it

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welcomes visitors and introduces the purpose of the site, or the organization sponsoring it, and then provides links to other pages within the site (Source: IAB) (see Chapter 2 model). Host: any computer on a network that offers services or connectivity to other computers on the network. A host has an IP address associated with it (Source: IAB) (see Chapter 2 model). House ad: self-promotional ad a company runs on their own site/network to use unsold inventory. Revenues from house ads should not be included in reported revenues (Source: modified from Marketing Terms.com and IAB) (see Chapter 2 model). Human information processing: theory that deals with how people receive, store, integrate, retrieve, and use information (see Chapter 3 keywords). Hybrid pricing: pricing model based on a combination of a CPM pricing model and a performance-based pricing model. See CPM pricing model and performance-based pricing model (Source: IAB) (see Chapter 6 BAM!). Hyperlink: a clickable link (e.g., on a Web page or within an e-mail) that sends the user to a new URL when activated (Source: IAB) (see Chapter 2 model). Hypertext: any text that contains links connecting it with other texts or files on the Internet (Source: IAB) (see Chapter 2 model). IAB: Interactive Advertising Bureau (http://www.iab.net) (Source: WebTrends) (see Chapter 6 BAM!). Impression: a single instance of an online advertisement being displayed (Source: Marketing Terms.com) (see Chapter 7 analytics). Impression fraud: the act of deliberately generating impressions of an advert without the intention of clicking on the advert. The result is a reduction in click-through rate, which can affect Quality Score in PPC advertising (Source: Quirk) (see Chapter 7 analytics). Inbound link: an inbound link is a hyperlink to a particular Web page from an outside site, bringing traffic to that Web page. Inbound links are an important element that most search engine algorithms use to measure the popularity of a Web page (Source: Search Engine Watch) (see Chapter 2 model). Incentivized traffic: visitors who have received some form of compensation for visiting a site (Source: Marketing Terms.com) (see Chapter 2 model). Information: in general, raw data that has been verified to be accurate and timely, is specific and organized for a purpose, is presented within a context that gives it meaning and relevance, and leads to an increase in understanding and decrease in uncertainty. The value of information lies solely in its ability to affect a behavior, decision, or outcome. A piece of information is considered valueless if, after receiving it, things remain unchanged (Source: BusinessDictionary) (see Chapter 2 keywords). Information access: the findability of information regardless of format, channel, or location (Source: AIM) (see Chapter 3 keywords). Information asymmetry: an imbalance of information in a marketplace (see Chapter 5 customers).

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Information foraging theory: theory that applies the ideas from optimal foraging theory to understand how human users search for information. The theory is based on the assumption that, when searching for information, humans use “built-in” foraging mechanisms that evolved to help our animal ancestors find food. Importantly, better understanding of human search behavior can improve the usability of Web sites or any other user interface (Source: Wikipedia) (see Chapter 3 keywords). Information overload: refers to the difficulty a person can have understanding an issue and making decisions that can be caused by the presence of too much information (see Chapter 5 customers). Information retrieval: a field of study related to information extraction. Information retrieval is about developing systems to effectively index and search vast amounts of data (Source: SearchEngineDictionary.com) (see Chapter 3 keywords). Information scent: cues related to the desired outcome (see Chapter 3 keywords). Information searching: refers to people’s interaction with information-retrieval systems, ranging from adopting search strategy to judging the relevance of information retrieved (see Chapter 3 keywords). Insertion: actual placement of an ad in a document, as recorded by the ad server (Source: IAB) (see Chapter 2 model). Insertion order: purchase order between a seller of interactive advertising and a buyer (usually an advertiser or its agency) regarding the insertion date(s), number of insertions in a stated period, ad size (or commercial length), and ad placement (or time slot). In effect, it is a purchase order and is issued typically through an advertising agency or a media representative (Source: modified from IAB) (see Chapter 2 model). Integrated marketing communications (IMC): the coordination and integration of all marketing communication tools, avenues, functions, and sources within a company into a seamless program that maximizes the impact on consumers and other end-users at a minimal cost (see Chapter 6 BAM!). Integrated results listing: multiple results from federated content collections shown on the same SERP (see Chapter 4 ads). Interactive advertising: all forms of online, wireless, and interactive television advertising, including banners, sponsorships, e-mail, keyword searches, referrals, slotting fees, classified ads, and interactive television commercials (Source: IAB) (see Chapter 6 BAM!). Internal page impressions: Web site activity that is generated by individuals with IP addresses known to be affiliated with the Web site owner. Internal activity associated with administration and maintenance of the site should be excluded from the traffic or measurement report (Source: IAB) (see Chapter 7 analytics). Internet marketing: marketing efforts done solely over the Internet. This type of marketing uses various online advertisements to drive traffic to an advertiser’s Web site. Banner advertisements, pay per click (PPC), and targeted e-mail lists are often methods used in Internet marketing to bring the most value to the advertiser.

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Internet marketing is a growing business mainly because more and more people use the Internet every day. Popular search engines such as Google and Yahoo have been able to capitalize on this new wave of advertising (Source: BusinessDictionary) (see Chapter 6 BAM!). Inventory: the number of ads available for sale on a Web site (Source: IAB) (see Chapter 2 model). Invisible Web: a term that refers to the vast amount of information on the Web that is not indexed by search engines. (Source: Search Engine Watch). IP Address: an abbreviation for Internet Protocol address, it is a unique combination of numbers assigned to individual electronic devices or networks that communicate over the Internet. Basically, it is a trackable address for any computer, and it can be used to localize results. The Internet Assigned Numbers Authority (IANA) oversees global IP address allocation. The format of an IP address is a 32-bit numeric address, written as four numbers separated by periods. Each number can be zero to 255. For example, 1.160.10.240 could be an IP address (Source: SEMPO and Wikipedia) (see Chapter 2 model). KEI analysis: Keyword Effectiveness Indicator. It is designed to measure and quantify the quality and worth of a search term (Source: Quirk) (see Chapter 7 analytics). Key performance indicators (KPIs): metrics used to quantify objectives that reflect the strategic performance of your online marketing campaigns. They provide business and marketing intelligence to assess a measurable objective and the direction in which that objective is headed (Source: SEMPO) (see Chapter 7 analytics). Keyphrase: words that are utilized by search engine advertisers to link to query terms (see Chapter 3 keywords). Keyword: a specific word or combination of words that a searcher might type into a search field. Includes generic, category keywords, industry-specific terms, product brands, common misspellings and expanded variations (called Keyword Stemming), or multiple words (called Long Tail for their lower CTRs but sometimes better conversion rates). All might be entered as a search query. For example, someone looking to buy coffee mugs might use the keyword phrase “ceramic coffee mugs.” Also, keywords that trigger ad network and contextual network ad serves are the auction components on which PPC advertisers bid for all Ad Groups/Orders and campaigns (Source: SEMPO) (see Chapter 3 keywords). Keyword density: the number of times a keyword or keyword phrase is used in the body of a page. This is a percentage value determined by the number of words on the page, as opposed to the number of times the specific keyword appears within it. In general, the higher the number of times a keyword appears in a page, the higher its density. This, divided by the total number of words that appear on a page, gives you a percentage. The higher the better, but not too high (Source: modified from SEMPO and Quirk) (see Chapter 4 ads). Keyword frequency: the number of times a keyword or keyphrase appears on a Web site (Source: Quirk) (see Chapter 4 ads).

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Keyword marketing: putting your message in front of people who are searching using particular keywords and keyphrases (Source: Marketing Terms.com) (see Chapter 6 BAM!). Keyword rankings: this term refers to where the keywords/phrases targeted by your SEO efforts rank among the search engines. If your targeted terms do not appear on the first three pages, start worrying (Source: Quirk) (see Chapter 4 ads). Keyword research: the process of researching what searchers are actually searching for and the analysis of which keywords yield the highest return on investment (ROI). Copy optimization revolves around the selection of the best keywords/keyphrases (Source: modified from Quirk and Marketing Terms.com) (see Chapter 3 keywords). Keyword stemming: to return to the root or stem of a word and build additional words by adding a prefix or suffix or pluralizing. The word can expand in either direction and even add words, increasing the number of variable options (Source: SEMPO) (see Chapter 3 keywords). Keyword stuffing: generally refers to the act of adding an inordinate number of keyword terms into the HTML or tags of a Web page (Source: SEMPO) (see Chapter 4 ads). Keyword tag: refers to the META keywords tag within a Web page. This tag is meant to hold approximately eight to ten keywords or keyword phrases, separated by commas. These phrases should be either misspellings of the main page topic or terms that directly reflect the content on the page on which they appear. Keyword tags are sometimes used for internal search results as well as viewed by search engines (Source: SEMPO) (see Chapter 4 ads). Keyword targeting: displaying pay-per-click search ads on publisher sites across the Web (see also Contextual Networks) that contain the keywords in a context advertiser’s Ad Group (Source: SEMPO) (see Chapter 2 model). Lag: the delay between making an online request or command and receiving a response. See latency (Source: IAB) (see Chapter 2 model). Landing page/Destination page: the Web page at which a searcher arrives after clicking on an ad. When creating a PPC ad, the advertiser displays a URL (and specifies the exact page URL in the code) on which the searcher will land after clicking on an ad in the SERP. Landing pages are also known as “where the deal is closed,” as it is landing page actions that determine an advertiser’s conversion rate success (Source: SEMPO) (see Chapter 4 ads). Latency: 1) time it takes for a data packet to move across a network connection; 2) visible delay between request and display of content and ad. Latency sometimes leads to the user leaving the site prior to the opportunity to see. In streaming media, latency can create stream degradation if it causes the packets, which must be received and played in order, to arrive out of order (Source: IAB) (see Chapter 2 model). Lead: a potential customer (Source: Quirk) (see Chapter 5 customers). Lead generation: fees advertisers pay to Internet advertising companies that refer qualified purchase inquiries (e.g., auto dealers that pay a fee in exchange

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for receiving a qualified purchase inquiry online) or provide consumer information (demographic, contact, and behavioral) where the consumer opts into being contacted by a marketer (e-mail, postal, telephone, and fax). These processes are priced on a performance basis (e.g., cost per action, lead, or inquiry) and can include user applications (e.g., for a credit card), surveys, contests (e.g., sweepstakes), or registrations (Source: IAB) (see Chapter 6 BAM!). Link: a clickable connection between two Web sites. Formally referred to as a hyperlink. If you click on the link, you will be taken to that page (Source: modified from IAB and Quirk) (see Chapter 2 model). Link bait: editorial content, often sensational in nature, posted on a Web page and submitted to social media sites in hopes of building inbound links from other sites (Source: Search Engine Watch) (see Chapter 4 ads). Link building: the process of getting quality Web sites to link to your Web site to improve search engine rankings. Link-building techniques can include buying links, reciprocal linking, or entering barter arrangements (Source: Search Engine Watch) (see Chapter 2 model). Listing: a series of results shown on a SERP (see Chapter 4 ads). Load time: the length of time it takes for a page to open completely in the browser window (Source: Quirk) (see Chapter 2 model). Log analyzer: software that provides information about a site’s visitors, activity statistics, accessed files, click-through paths, and other analytical data based on the user’s behavior (Source: Quirk) (see Chapter 7 analytics). Log file: a file that records transactions that have occurred on the Web server. Some of the types of data collected are: date/time stamp, URL served, IP address of requestor, status code of request, user agent string, and previous URL of requestor. Use of the extended log file format is preferable (Source: IAB) (see Chapter 7 analytics). Log file analysis: the analysis of records stored in the log file. In its raw format, the data in the log files can be hard to read and overwhelming. There are numerous log file analyzers that convert log file data into user-friendly charts and graphs. A good analyzer is generally considered an essential tool in SEO because it can show search engine statistics such as the number of visitors received from each search engine, the keywords each visitors used to find the site, visits by search engine spiders, and so on (Source: SEMPO) (see Chapter 7 analytics). Logarithmic chart: a chart for which the price scale (usually on the vertical axis) is skewed so that a given distance always represents the same percentage change in price rather than the same absolute change in price (as is the case for a linear chart). In other words, the distance from 1 to 10 is the same as the distance from 10 to 100 on a logarithmic chart, but the latter distance is ten times greater on a linear chart (Source: BusinessDictionary) (see Chapter 3 keywords). Long tail: keyword phrases with at least three, sometimes four or five, words in them. These long-tailed keywords are usually highly specific and draw lower traffic than shorter, more competitive keyword phrases, which is why they are also cheaper.

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Oftentimes, long-tailed keywords, in aggregate, have good conversion ratios for the low number of click-throughs they generate (Source: SEMPO) (see Chapter 3 keywords). Long-tailed keywords: keyword phrases with at least two or three words in them. (Source: SEMPO) (see Chapter 3 keywords). Long-Term Value or Life-Time Value (LTV): metric used to describe the value a specific customer has over the life of their relationship with you (Source: WebTrends) (see Chapter 6 BAM!). Marketing: Management process through which goods and services move from concept to the customer. As a philosophy, it is based on thinking about the business in terms of customer needs and their satisfaction. As a practice, it consists in coordination of four elements called 4P’s: (1) a product, (2) its price, (3) distribution to a place, and (4) development of a promotion (Source: BusinessDictionary.com) (see Chapter 6 BAM!). Marketing mix: the four elements businesses need to consider for the success of their marketing efforts: product, price, place, and promotion. The focus and strategy that is placed on each one is entirely dependent on the goals of the marketing strategy (Source: Quirk) (see Chapter 6 BAM!). Marketing performance management (MPM): drives stronger customer relationships and higher life-time value based on a framework of established goals, consistent metrics, and constant optimization across the entire marketing organization and across every customer touch point (Source: WebTrends) (see Chapter 6 BAM!). Marketing plan: a written document detailing the actions necessary to achieve marketing objectives (Source: Quirk) (see Chapter 6 BAM!). Match: A match occurs when a document in the search engine’s index contains terms entered as part of the query. The matching documents, simply called matches, are then displayed on the SERP. It is worth noting that search engines have different criteria for deciding when a document is a match. Most search engines only require that one word in the query match one word in the document. Some search engines (like Google) require all words to appear in the document before that document is considered a match (Source: SearchEngineDictionary.com) (see Chapter 2 model). Media agency: is a company that helps companies communicate with current and potential consumers and/or the general public (Source: Wikipedia) (see Chapter 6 BAM!). Merchant: this is the owner of the product that is being marketed or promoted. Also referred to as advertiser (Source: Quirk) (see Chapter 6 BAM!). Meta data: data about information. Information that can be entered about a Web page and the elements on it that provide context and relevancy information to search engines. This used to be an all-important ranking factor (Source: modified from Quirk) (see Chapter 2 model). Meta tags: information placed in the HTML header of a Web page, providing information that is not visible to browsers, but can be used in varying degrees by search engines

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to index a page. Common meta tags used in search engine marketing are title, description, and keyword tags (Source: Search Engine Watch) (see Chapter 2 model). Metrics: a system of parameters or ways of quantitative assessment of a process that is to be measured, along with the processes to carry out such measurement. Metrics define what is to be measured (Source: WebTrends) (see Chapter 7 analytics). Minimum bid: the least amount that an advertiser can bid for a keyword or keyword phrase and still be active on the search ad network. This amount can vary and is set by the search engine (Source: modified SEMPO) (see Chapter 8 auctions). Mobile search: an evolving branch of information-retrieval services centered on the convergence of mobile platforms and mobile handsets or other mobile devices. The services allow users to find mobile content interactively on mobile Web sites, and mobile content shows a media shift toward mobile multimedia (Source: WebTrends) (see Chapter 10 future). Multivariate testing: a test using many variables to determine statistically significant influences on outcomes. A type of testing that varies and tests more than one or two campaign elements at a time to determine the best performing elements and combinations. Multivariate testing can gather significant results on many different components of, for example, alternative PPC ad titles or descriptions in a short period of time. Often it requires special expertise to analyze complex statistical results. (Compare to A/B Testing, which changes only one element at a time, alternately serving an “old” version ad and a changed ad.) In search advertising, you might do A/B Split or Multivariate testing to learn what parts of a landing page (background color, title, headline, fill-in forms, design, and images) produce higher conversions and are more cost-effective (Source: modified from SEMPO and Quirk) (see Chapter 7 auctions). Navigation: the act of moving from location to location within a Web site, or between Web sites, accomplished by clicking on links. Navigation can also refer to the overall structure of the links on the site, comprising the paths available to the visitor (Source: WebTrends) (see Chapter 9 framework). Negative keywords: filtered-out keywords to prevent ad serves on them in order to avoid irrelevant click-through charges or to refine and narrow the targeting of your keywords. Formatting negative keywords varies by search engine, but they are usually designated with a minus sign (Source: modified SEMPO) (see Chapter 3 keywords). Network effect: the phenomenon whereby a service becomes more valuable as more people use it, thereby encouraging ever-increasing numbers of adopters (Source: MarketingTerms.com) (see Chapter 2 model). New visitor: a unique visitor who visits a Web site for the first time ever in the period of time being analyzed (Source: Quirk) (see Chapter 7 analytics). Nonqualifying page impressions: page impressions that should be excluded from traffic or measurement reports, such as unsuccessful transfers of requested documents, successful transfers of requested documents to a robot or spider, and/or pages in a frame set. See frames (Source: IAB) (see Chapter 7 analytics).

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North: the advertisements shown at the top of a SERP (see Chapter 4 ads). Off the page/off-the-page factors/off-the-page criteria: those factors that impact the ranking of a Web page but that are not located on the Web page itself. Inbound links and anchor text are examples of off-the-page factors (Source: SearchEngineDictionary. com) (see Chapter 2 model). Off-site measurement: when a site forwards its log files to an off-site Web research service for analysis (Source: IAB) (see Chapter 7 analytics). On-demand: the ability to request video, audio, or information to be sent to the screen immediately by clicking something on the screen referring to that choice (Source: IAB) (see Chapter 2 model). On-site measurement: when a server has an appropriate software program to measure and analyze traffic received on its own site (Source: IAB) (see Chapter 7 analytics). Ontology: in the context of search engines, it refers specifically to a file that defines relationships between words (Source: SearchEngineDictionary.com) (see Chapter 2 keywords). Optimization: marketing technology through which the best possible ad placement is automatically determined based on advertiser and publisher objectives, and varied according to observed performance. Finding an alternative with the most cost-effective or highest achievable performance under the given constraints by maximizing desired factors and minimizing undesired ones. In comparison, maximization means trying to attain the highest or maximum result or outcome without regard to cost or expense. Practice of optimization is restricted by the lack of full information and the lack of time to evaluate what information is available (see bounded reality for details). In computer simulation (modeling) of business problems, optimization is achieved usually by using linear programming techniques of operations research (Source: modified from Advertising.com and BusinessDictionary) (see Chapter 7 analytics). Opt-in: refers to an individual giving a company permission to use data collected from or about the individual for a particular reason, such as to market the company’s products and services. See permission marketing (Source: IAB) (see Chapter 6 BAM!). Opt-out: when a company states that it plans to market its products and services to an individual unless the individual asks to be removed from the company’s mailing list (Source: IAB) (see Chapter 6 BAM!). Organic listings: listings that appear solely because a search engine has deemed it editorially important for them to be included, regardless of payment (Source: SEMPO) (see Chapter 2 model). Organic results: listings on SERP that were not paid for; listings for which search engines do not sell space. Sites appear in organic (also called “natural”) results because a search engine has applied formulas (algorithms) to its search crawler index, combined with editorial decisions and content weighting, that it deems important enough inclusion without payment. Paid Inclusion Content is also often considered

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“organic,” even though it is paid advertising, because paid inclusion content usually appears on SERPs mixed with unpaid, organic results (Source: SEMPO) (see Chapter 2 model). Organic search: the listings generally found on the left-hand side of a SERP and not influenced by direct financial payments. These listings are results based on factors such as keyword relevancy within a Web page. SEO is used to boost success (Source: Quirk) (see Chapter 2 model). Page: unit of content (so downloads and Flash files can be defined as a page). A document having a specific URL and comprised of a set of associated files. A page may contain text, images, and other online elements. It may be statically or dynamically generated. It may be made up of multiple frames or screens, but should contain a designated primary object that, when loaded, is counted as the entire page (Source: modified from Quirk and IAB) (see Chapter 2 model). Page display: when a page is successfully displayed on the user’s computer screen (Source: IAB) (see Chapter 2 model). Page impression: a measurement of responses from a Web server to a page request from the user’s browser, which is filtered from robotic activity and error codes and is recorded at a point as close as possible to the opportunity to see the page by the user. See http://www.iab.net for ad campaign measurement guidelines (Source: IAB) (see Chapter 7 analytics). Page jacking: theft of a page from the original site and publication of a copy (or nearcopy) at another site (Source: Marketing Terms.com) (see Chapter 2 model). Page request: the opportunity for an HTML document to appear on a browser window as a direct result of a user’s interaction with a Web site (Source: IAB) (see Chapter 2 model). Page view: request to load a single HTML page (Source: Marketing Terms.com) (see Chapter 2 model). PageRank (PR): the Google technology developed at Stanford University for placing importance on pages and Web sites. At one point, PageRank (PR) was a major factor in rankings. Today it is one of hundreds of factors in the algorithm that determines a page’s rankings (Source: SEMPO) (see Chapter 2 model). Paid Inclusion: refers to the process of paying a fee to a search engine in order to be included in that search engine or directory. Also known as guaranteed inclusion. Paid inclusion does not impact rankings of a Web page; it merely guarantees that the Web page itself will be included in the index. These programs were typically used by Web sites that were not being fully crawled or were incapable of being crawled, due to dynamic URL structures, frames, and other factors (Source: SEMPO) (see Chapter 2 model). Paid listing: a listing on a SERP achieved through outbidding competitors (as in PPC). The term is sometimes also used to refer to keyword-targeted advertisements, where the advertiser pays the search engine a fixed amount to have its ad shown on the SERP for a specific keyword (Source: SearchEngineDictionary.com) (see Chapter 2 model).

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Paid placement: advertising program where listings are guaranteed to appear in response to particular search terms, with higher ranking typically obtained by paying more than other advertisers (Source: SEMPO) (see Chapter 2 model). Paid search: placing ads for products or services on SERPs (listings appear at the top of the page and on the right-hand side) and on content sites across the Internet. These ads are typically small snippets of text linked to merchandise pages (Source: Quirk) (see Chapter 2 model). Palming off: to misrepresent inferior goods of one producer as superior goods made by a reputable, well-regarded competitor in order to gain commercial advantage and promote sales (see Chapter 6 BAM!). Parameters: these are located in the URL immediately after a question mark and followed by an equal sign and a return value, known as name=value (Source: WebTrends) (see Chapter 2 model). Pass-along rate: the percentage of people who pass on a message or file (Source: Marketing Terms.com) (see Chapter BAM!). Path: a path is the click pattern a visitor uses as they traverse through multiple pages (Source: WebTrends) (see Chapter 2 model). Pay per call: a model of paid advertising similar to Pay Per Click (PPC), except advertisers pay for every phone call that comes to them from a search ad, rather than for every click-through to their Web site landing page for the ad. Often costs higher than PPC advertising, but valued by advertisers for higher conversion rates from consumers who take the action step of telephoning an advertiser (Source: SEMPO) (see Chapter 2 model). Pay per click (PPC): online advertising payment model in which payment is based solely on qualifying click-throughs (Source: Marketing Terms.com) (see Chapter 2 model). Pay-per-click model: the most common payment method, although others are also utilized, such as pay-for-impression, pay-per-action, and pay-per-call (see Chapter 2 model). Pay-per-click search engine (PPCSE): search engine where results are ranked according to the bid amount and advertisers are charged only when a searcher clicks on the search listing (Source: Marketing Terms.com) (see Chapter 2 model). Pay per impression: an advertising pricing model in which advertisers pay based on how many users were served from their ads (Source: IAB) (see Chapter 2 model). Pay per lead (PPL): online advertising payment model in which payment is based solely on qualifying leads (Source: Marketing Terms.com) (see Chapter 2 model). Pay per sale (PPS): online advertising payment model in which payment is based solely on qualifying sales (Source: Marketing Terms.com) (see Chapter 2 model). Payment threshold: the minimum accumulated commission an affiliate must earn to trigger payment from an affiliate program (Source: Marketing Terms.com) (see Chapter 2 model).

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Perceived marginal utility: gratification received from consuming the next unit of a good (see Chapter 6 BAM!). Performance pricing model: an advertising model in which advertisers pay based on a set of agreed-on performance criteria, such as a percentage of online revenues or delivery of new sales leads. Examples are CPA, CPC, CPL, CPO, CPS, and CPT (Source: IAB) (see Chapter 2 model). Performance-based advertising: advertising model in which the advertiser pays based on results achieved (Source: Advertising.com) (see Chapter 2 model). Permission marketing: marketing centered on getting customer’s consent to receive information from a company (Source: Marketing Terms.com) (see Chapter 6 BAM!). Persistent cookie: cookies that remain on a client’s hard drive until they expire (as determined by the Web site that set them) or are deleted by the end-user (Source: IAB) (see Chapter 2 model). Personal Experience Factor (PEF): the customer’s interaction with a Web site, ad, or brand (Source: WebTrends) (see Chapter BAM!). Personas: these are “people types” or subgroups that encompass several attributes such as gender, age, location, salary level, leisure activities, lifestyle characteristics, marital/family status, or some kind of definable behavior. Useful profiles for focusing ad messages and offers to targeted segments (Source: SEMPO) (see Chapter 5 customers). Platform: the type of computer or operating system on which a software application runs, (e.g., Windows, Macintosh or Unix) (Source: IAB) (see Chapter 2 model). Pop-under ad: an ad that displays in a new browser window behind the current browser window (Source: Marketing Terms.com) (see Chapter 2 model). Pop-up ad: an ad that displays in a new browser window (Source: Marketing Terms. com) (see Chapter 2 model). Portal: a site featuring a suite of commonly used services, serving as a starting point and frequent gateway to the Web (Web portal) or a niche topic (vertical portal) (Source: Marketing Terms.com) (see Chapter 2 model). Position: in PPC advertising, position is the placement on a search engine results page where your ad appears relative to other paid ads and organic search results. Top-ranking paid ads (high-ranking ten to fifteen results, depending on the engine) usually appear at the top of the SERP and on the “right rail” (right-side column of the page). Ads appearing in the top slots or “north” are known as premium positions. Paid search ad position is determined by confidential algorithms and quality score measures specific to each search engine. However, factors in the engines’ position placement under some advertiser control include bid price, the ad’s CTR, relevancy of your ad to searcher requests, relevance of your click-through landing page to the search request, and quality measures search engines calculate to ensure quality user experience (Source: modified from SEMPO) (see Chapter 4 ads).

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Position preference: a feature in sponsored search systems enabling advertisers to specify in which positions they would like their ads to appear on the SERP. Not a position guarantee (Source: modified from SEMPO) (see Chapter 8 auctions). Potential customer: a consumer that may become but is not yet a customer (see Chapter 5 customers). Power laws: mathematical relationship between two quantities. When the frequency of an event varies as a power of some attribute of that event (e.g., its size), the frequency is said to follow a power law (see Chapter 3 keywords). PPC advertising: acronym for Pay-Per-Click Advertising, a model of online advertising in which advertisers pay only for each click on their ads that directs searchers to a specified landing page on the advertiser’s Web site. PPC ads may get thousands of impressions (views or serves of the ad); however, unlike more traditional ad models billed on a CPM (Cost-Per-Thousand-Impressions) basis, PPC advertisers only pay when their ad is clicked on. Charges per ad click-through are based on advertiser bids in hybrid ad space auctions and are influenced by competitor bids, competition for keywords, and search engines’ proprietary quality measures of advertiser ad and landing page content (Source: SEMPO) (see Chapter 6 BAM!). PPC management: the monitoring and maintenance of a Pay-Per-Click campaign or campaigns. This includes changing bid prices, expanding and refining keyword lists, editing ad copy, testing campaign components for cost effectiveness and successful conversions, and reviewing performance reports for reports to management and clients, as well as results to feed into future PPC campaign operations (Source: SEMPO) (see Chapter 2 model). Process audit: third-party validation of internal control processes associated with measurement. See audit (Source: IAB) (see Chapter 7 analytics). Profiling: the practice of tracking information about consumers’ interests by monitoring their movements online. This can be done without using any personal information, but simply by analyzing the content, URLs, and other information about a user’s browsing path/click-stream (Source: IAB) (see Chapter 5 customers). Profit: money made from a product/service after expenses have been accounted for (Source: Quirk) (see Chapter 2 model). Prospect: the visitor who reaches an intent-to-transact page (for example, a page with a shopping cart or a form) (see Chapter 5 customers). Protocol: an established method of exchanging data over the Internet (Source: WebTrends) (see Chapter 2 model). Publisher: an individual or organization that prepares, issues, and disseminates content for public distribution or sale via one or more media (Source: IAB) (see Chapter 2 model). Purchase point: a point in time or location where sales are made (see Chapter 2 model). Quality score: basis for measuring the quality of keywords and determining minimum PPC bids. This score is calculated by measuring a keyword’s click-through

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rate, ad text relevancy, the keyword’s historical performance, and the quality of the landing page (Source: Quirk) (see Chapter 4 ads). Query: a series of terms entered by a searcher into a search engine. The keyword or keyword phrase a searcher enters into a search field, which initiates a search and results in a SERP with organic and paid listings (Source: SEMPO) (see Chapter 3 keywords). Query length: the number of terms in a query (see Chapter 3 keywords). Query parameter: an individual piece of a query string consisting of a parameter name and a value for the parameter (Source: WebTrends) (see Chapter 3 keywords). Rank: a measure of which position an ad is in the SERP listings. How well positioned a particular Web page or Web site appears in search engine results. For example, if you rank at position #1, you are the first listed paid or sponsored ad. If you are in position #18, it is likely that your ad appears on the second or third page of search results, after seventeen competitor paid ads and organic listings. Rank and position affect your click-through rates and, ultimately, conversion rates for your landing pages (Source: SEMPO) (see Chapter 4 ads). Ranking: in search, ranking is used to describe the relative position of a Web page in the SERPs (Source: Quirk) (see Chapter 4 ads). Rational actor: a value-maximizing unit in the sense that, with respect to the actor’s own values and preferences, the actor makes choices in such a way as to maximize outcomes (see Chapter 5 customers). Reach: the estimated number of individuals in the audience. The size of the audience reading, viewing, hearing, or interacting with a message in a given period of time. Reach can be understood as either an absolute number or a fraction of a population (Source: WebTrends) (see Chapter 6 BAM!). Real time: events that happen live at a particular moment. When one chats in a chat room, or sends an instant message, one is interacting in real time (Source: IAB) (see Chapter 2 model). Recency: the number of days since a visitor’s most recent visit during a reporting period. See also frequency (Source: WebTrends) (see Chapter 5 customers). Referral fees: fees paid by advertisers for delivering a qualified sales lead or purchase inquiry (Source: IAB) (see Chapter 2 model). Referral link: the referring page or referral link is a place from which the user clicked to get to the current page. In other words, because a hyperlink connects one URL to another, in clicking on a link the browser moves from the referring URL to the destination URL. Also known as source of a visit (Source: IAB) (see Chapter 2 model). Relative conversion rate: The expected change in conversion rate in relation to rank 1 (see Chapter 7 analytics). Relevance: describes how pertinent, connected, or applicable something is to a given matter. The measure of the accuracy of the search results; in other words, it is a measure of how close the documents listed in the search results are to what the user was looking for (Source: SearchEngineDictionary.com) (see Chapter 4 ads).

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Repeat visitor: unique visitor who has accessed a Web site more than once over a specific time period (Source: IAB) (see Chapter 7 analytics). Research shopper: research shopper phenomenon, which is the tendency of some consumers to research the product in one channel (e.g., the Web) and then purchase it through another channel (e.g., a store) (see Chapter 5 customers). Results: the listings shown on a SERP in response to a query (see Chapter 2 model). Return on advertising (ROA): the revenue generated by advertising spent (see Chapter 7 analytics). Return on advertising spending (ROAS): represents the dollars earned per dollars spent on the corresponding advertising (Source: Internet Marketing Glossary) (see Chapter 2 model). Return on investment (ROI): the amount of money an advertiser earns from its ads compared to the amount of money the advertiser spends on ads (Source: Search Engine Watch) (see Chapter 7 analytics). Return visitor: a unique visitor who is not a new visitor to the site (Source: Quirk) (see Chapter 7 analytics). Return visits: the average number of times a user returns to a site over a specific time period (Source: IAB) (see Chapter 7 analytics). Revenue: yield of income from a particular source (Source: Quirk) (see Chapter 2 model). Revenue per thousand impressions (RPI): yield from the display of 1,000 advertisements (see Chapter 7 analytics). Revenue per search (RPS): yield from the submission of one query to a search engine by a searcher (see Chapter 2 model). Revshare/revenue sharing: a method of allocating per-click revenue to a site publisher and click-through charges to a search engine that distributes paid ads to its context network partners, for every page viewer who clicks on the content site’s sponsored ads. A type of site finder’s fee (Source: SEMPO) (see Chapter 2 model). Right rail: the advertisements along the right side of the search engine results page. Also known as east. The common name for the right-side column of a Web page. On a SERP, the right rail is usually where sponsored listings appear (Source: modified from SEMPO) (see Chapter 4 ads). ROI timelag: the period from when advertising dollars are spent and when revenue is generated (see Chapter 2 model). Sample: in statistics, a subset of a universe whose properties are studied to gain information about that universe (Source: IAB) (see Chapter 7 analytics). Sampling: in statistics, the selection of individual observations intended to yield knowledge about a population, especially for the purposes of statistical inference (Source: WebTrends) (see Chapter 7 analytics). Scenario analysis: a report showing the amount of activity at each step of a defined scenario, plus conversion rates for each transition from step to step as well as for

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the whole process. Examples of scenarios are check-out, registration, or application sequences (Source: WebTrends) Score: search engines usually arrange search results from the most relevant to the least relevant (as determined by the search engine’s algorithm). To rank documents, the search engine assigns a score to each page, and those with the highest scores are listed first. Most search engines simply give the maximum score to the most relevant document and score all other relevant documents relative to that document. Others compare all documents to a theoretically perfect document. The score of a Web page therefore refers to its relevance as perceived by a specific search engine (Source: SearchEngineDictionary. com) (see Chapter 2 model). Screen real estate: the area of pixels on a SERP (see Chapter 2 model). Search: the process of finding information on the Internet using search engines (Source: modified from Quirk) (see Chapter 3 keywords). Search advertising: an advertiser bids for the chance to have their ad display when a user searches for a given keyword. These are usually text ads, which are displayed above or to the right of the algorithmic (organic) search results. Most search ads are sold by the PPC model, where the advertiser pays only when the user clicks on the ad or text link (Source: Search Engine Watch) (see Chapter 2 model). Search box: where the searcher enters the query on the search engine Web page (see Chapter 2 model). Search engine: a program that indexes documents and then attempts to match documents by relevancy to the users’ search requests (Source: Marketing Terms.com) (see Chapter 2 model). Search engine listing: the listing of pages on the search engine results page (SERP) (Source: Quirk) (see Chapter 2 model). Search engine marketing (SEM): the act of marketing a Web site via search engines, whether this be improving rank in primarily purchasing paid listings (PPC management), but also organic listings (search engine optimization), or a combination of these and other search engine-related activities (i.e., affiliate programs, shopping feeds, or link development). An Internet marketing method that focuses on purchasing ads that appear on the result pages of search engines such as Google. Many search engines offer ways for individuals or businesses to purchase ads that typically appear above or to the right of the content on the search result pages. Typically, the higher the fee one offers to pay for an ad, the higher the ad will appear on the page, depending on how much competition there is to appear on that page. Depending on the agreement, one may pay a flat fee for a given length of time, or may pay a given fee for each click that they receive to their ad (Source: modified from WebTrends and BusinessDictionary) (see Chapter 2 model). Search engine optimization (SEO): the act of altering a Web site so that it does well in the organic, crawler-based listings of search engines. In the past, has also been used as a term for any type of search engine marketing activity, although now “search engine marketing” is more commonly used as an umbrella term. It refers to the process of

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improving traffic to a given Web site by increasing the site’s visibility in search engine results. Web sites improve search engine optimization by improving content, making sure that the pages can be indexed correctly, and ensuring that the content is unique. Going through the search engine optimization process typically leads to more traffic for the site because the site will appear higher in search results for information that pertains to the site’s offerings (Source: modified from WebTrends and BusinessDictionary) (see Chapter 2 model). Search engine positioning (SEP): synonymous with SEO, search engine positioning is the act of altering a Web site to perform well in organic or natural search results (Source: WebTrends) (see Chapter 2 model). Search engine results page (SERP): the page searchers see after they have entered their query into the search box. This page lists several Web pages related to the searcher’s query, sorted by relevance. Increasingly, search engines are returning blended search results, which include images, videos, and results from specialty databases on their SERPs (Source: Search Engine Watch) (see Chapter 2 model). Search engine spam: excessive manipulation to influence search engine rankings, often for pages that contain little or no relevant content (Source: Marketing Terms. com) (see Chapter 2 model). Search engine submission: the act of supplying a URL to a search engine in an attempt to make a search engine aware of a site or page (Source: Marketing Terms. com) (see Chapter 2 model). Search funnel: movement of searchers, who tend to do several searches before reaching a buy decision, which works from broad, general keyword search terms to narrower, specific keywords. Advertisers use the search funnel to anticipate customer intent and develop keywords targeted to different stages. Also refers to potential for switches at stages in the funnel when, for example, searchers start with keywords for a desired brand but switch to other brands after gathering information on the category (Source: SEMPO) (see Chapter 5 customers). Search marketer: Whether in SEO, PPC, or both, a search marketer uses search engines to sell products, channel traffic, and heighten brand awareness (Source: Quirk) (see Chapter 6 BAM!). Search marketing agency: an advertising agency that provides SEM services (see Chapter 6 BAM!). Search personalization: the ability to personalize SERPs based on personal profile information, settings, or location (IP address) (Source: WebTrends) (see Chapter 10 future). Search query: the word or phrase a searcher types into a search field, which initiates search engine results page listings and PPC ad serves. In PPC advertising, the goal is to bid on keywords that closely match the search queries of the advertiser’s targets (Source: SEMPO) (see Chapter 3 keywords). Search results: the documents returned by a search engine in response to a query. Also see SERP (Source: SearchEngineDictionary.com) (see Chapter 2 model).

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Search terms: words entered by the searcher. Search engines will then look for these words in their index and return matching results. Also known as search query (Source: Quirk) (see Chapter 3 keywords). Searcher: a person engaged in information searching (see Chapter 5 customers). Searching: exploration of the Web by following one interesting link to another, usually with a definite objective and a planned search strategy. In comparison, surfing is exploration definite in objective but not in strategy, and browsing is exploration without a definite objective or search strategy (Source: BusinessDictionary) (see Chapter 3 keywords). Second-price auction: an auction in which the bidder who submitted the highest bid is awarded the object being sold and pays a price equal to the second highest bid (see Chapter 8 auctions). Secondary research: collection of existing research data (Source: Quirk) (see Chapter 7 analytics). Segment: a grouping of customers, defined by Web site activity or other data that can be used to target them effectively (Source: WebTrends) (see Chapter 6 BAM!). Sell-through rate: the percentage of ad inventory sold as opposed to traded or bartered (Source: IAB) (see Chapter 2 model). Server-side: transactions that take place on the server (Source: Quirk) (see Chapter 2 model). Server-side tracking: the process of analyzing Web server log files. Server-side analytic tools make sense of raw data to generate meaningful reports and trends analysis (Source: SEMPO) (see Chapter 2 model). Session cookies: these are temporary and are erased when the browser exits at the end of a Web-surfing session (Source: IAB) (see Chapter 2 model). Session duration: the period that a session lasts (see Chapter 2 model). Session IDs: dynamic parameters, such as session IDs generated by cookies for each individual user. Session IDs cause search engines to see a different URL for each page each time that they return to recrawl a Web site (Source: SEMPO) (see Chapter 2 model). Search session length: the number of queries in a session (see Chapter 2 model). Session: several meanings depending on context (Source: modified from IAB) (see Chapter 7 analytics): • A sequence of Internet activity made by one user at one site. If a user makes no request from a site during a thirty-minute period of time, the next content or ad request would then constitute the beginning of a new visit. • A series of transactions performed by a user that can be tracked across successive Web sites. For example, in a single session, a user may start on a publisher’s Web site, click on an advertisement, and then go to an advertiser’s Web site and make a purchase. • A sequence of queries submitted by a searcher in one period of interaction with a search engine and around a similar topic.

Glossary

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Sessionization: this is the process for creating a session. Sessionization methods are ways in which you can define a session. Web analytics solutions have multiple sessionization methods such as cookies, IP Address, IP+ Agent, and so on. These methods tell the Web analytics system how they should count a series of page requests from the same individual or browsing machine (Source: WebTrends) (see Chapter 7 analytics). Shopping bot: intelligent agent that searches for the best price (Source: IAB) (see Chapter 2 model). Shopping search/feeds: shopping search engines allow shoppers to look for products and prices in a search environment for rapid and easy comparison. Premium placement can be purchased on some shopping search indices via XML feeds (Source: WebTrends) (see Chapter 3 keywords). Signal processing theory: deals with operations on or analysis of signals, in either discrete or continuous time, to perform useful operations on those signals (see Chapter 7 analytics). Simple reaction time (SRT): time it takes to react to stimuli (see Chapter 4 ads). Site optimization: the act of modifying a site to make it easier for search engines to automatically index the site and hopefully result in better placement in results (Source: modified from IAB) (see Chapter 2 model). Site-targeted ads: site targeting lets advertisers display their ads on manually selected sites in the search engine’s content network for content or contextual ad serves. Site-targeted ads are billed more like traditional display ads, per 1,000 impressions (CPM), and not on a Pay-Per-Click basis (Source: SEMPO) (see Chapter 4 ads). Skip word: a word that often appears in a page’s copy or content but has no significance by itself. Examples of skip words are: and, the, of, etc. (known in academia as stop words) (see Chapter 2 model). SKU: Stock Keeping Units (Source: WebTrends) (see Chapter 6 BAM!). SMEs: subject matter experts (see Chapter 6 BAM!). Social media: a category of sites that is based on user participation and user-generated content. They include social networking sites like LinkedIn or Facebook, social bookmarking sites like Del.icio.us, social news sites like Digg or Reddit, and other sites that are centered on user interaction (Source: Search Engine Watch) (see Chapter 10 future). Software as a service (SaaS): sometimes referred to as “software on demand,” it is software that is deployed over the Internet and/or is deployed to run behind a firewall on a local area network (LAN) or personal computer. With SaaS, a provider licenses an application to customers either as a service on-demand, through a subscription, on a “pay-as-you-go” basis, or (increasingly) at no charge. This approach to application delivery is part of the utility-computing model where all of the technology is in the “cloud” accessed over the Internet as a service (Source: Wikipedia). (see Chapter 2 model). South: the ads at the bottom of a SERP (see Chapter 4 ads).

266

Glossary

Space: location on a page of a site in which an ad can be placed. Each space on a site is uniquely identified. There can be multiple spaces on a single page (Source: IAB) (see Chapter 2 model). Spam: any search marketing method that a search engine deems to be detrimental to its efforts to deliver relevant, quality search results. Some search engines have written guidelines on their definitions and penalties for spam. Examples include doorway-landing pages designed primarily to game search engine algorithms rather than meet searcher expectations from the advertiser’s clicked-on ad; keyword stuffing in which search terms that motivated a click-through are heavily and redundantly repeated on a page in place of relevant content; attempts to redirect click-through searchers to irrelevant pages, product offers, and services; and landing pages that simply compile additional links on which a searcher must click to get any information. Determining what constitutes spam is complicated by the fact that different search engines have different standards, including what is allowable for listings gathered through organic methods versus paid inclusion (referred to as spamdexing), whether the listing is from a commercial or research/academic source, and so forth (Source: modified from SEMPO and Webmaster) (see Chapter 2 model). Spam filter: software built into e-mail gateways as well as e-mail client applications designed to identify and remove spam (Source: IAB) (see Chapter 2 model). Spamming: refers to a wide array of techniques used to “trick” the search engines. These tactics generally are against the guidelines put forth by the search engines. Tactics such as Hidden Text, Doorway Pages, Content Duplication, and Link Farming are but a few of many spam techniques employed over the years (Source: SEMPO) (see Chapter 2 model). Spend: the amount of money spent on an advertising effort (see Chapter 8 auctions). Spider: a program that crawls through the Web, visiting Web pages to collect information to add to or update a search engine’s index. The major search engines on the Web all have such a program, which is also known as a “crawler” or a “bot” (Source: Search Engine Watch) (see Chapter 2 model). Splash page: a branding page before the home page of a Web site (Source: Marketing Terms.com) (see Chapter 2 model). Sponsored links: the paid search results on a SERP (Source: Quirk) (see Chapter 2 model). Sponsored listing: a term used as a title or column head on a SERP to identify paid advertisers and distinguish between paid and organic listings (Source: modified from SEMPO) (see Chapter 2 model). Sponsored results: advertisements on a SERP (see Chapter 2 model). Sponsored search analytics: collecting, measuring, analyzing, and reporting keyword advertising data for purposes of monitoring, understanding, and optimizing search engine marketing (see Chapter 7 analytics).

Glossary

267

Sponsorship: association with a Web site in some way that gives an advertiser some particular visibility and advantage above that of run-of-site advertising (Source: IAB) (see Chapter 6 BAM!). Stakeholder: a person or organization with an interest (a “stake”) in how a resource is managed (Source: Quirk) (see Chapter 9 framework). Static ad placement: ad-serving approach through which ad placement is not altered based on performance factors commonly employed for sponsorships (i.e., ad placement does not vary according to resulting clicks or conversions, time of day, etc) (Source: Advertising.com) (see Chapter 2 model). Static keyword bidding: bidding approach through which term bids are not altered based on performance factors (i.e., bidding does not vary according to resulting clicks or conversions, time of day, etc) (Source: Advertising.com) (see Chapter 8 auctions). Statistical validity: the degree to which an observed result, such as a difference between two measurements, can be relied on and not attributed to random error in sampling or in measurement. Statistical validity is important to the reliability of test results, particularly in multivariate testing methods (Source: modified from UsabilityFirst.com and SEMPO) (see Chapter 7 analytics). Stickiness: a measure used to gauge the effectiveness of a site in retaining individual users. Stickiness is usually measured by the duration of the visit or the amount of time spent at a site over a given time period (Source: modified from Marketing Terms.com and IAB) (see Chapter 7 analytics). Stop word: a word that appears on a Web page that will stop a search engine from indexing that Web page (see Chapter 2 model). Submission: the act of submitting a Web site to search engines and search directories. For some search engines, this is performed simply by typing in the absolute home page URL of the Web site you wish to submit. Other engines and directories request that descriptions of the Web site be submitted for approval (Source: SEMPO) (see Chapter 2 model). Target audience: the intended audience for an ad, usually defined in terms of specific demographics (age, sex, income, etc.), product purchase behavior, product usage, or media usage (Source: IAB) (see Chapter 6 BAM!). Targeting: determining one’s niche marketing audience by narrowly focusing ads and keywords to attract a specific, marketing-profiled searcher and potential customer. You can target to geographic locations (geo-targeting), by days of the week or time of day (dayparting), or by gender and age (demographic targeting). Targeting features vary by search engine. Newer ad techniques and software focus on behavioral targeting based on Web activity and behaviors that are predictive for potential customers who might be more receptive to particular ads (Source: modified from SEMPO and Quirk) (see Chapter 6 BAM!). Taxonomy: a set of agreed-on principles according to which information can be stored more logically in an information-retrieval system. The term is used in science

268

Glossary

to describe the classification of natural elements (Source: SearchEngineDictionary. com) (see Chapter 3 keywords). Term: a series of characters, typically a word, used in a search query (see Chapter 3 keywords). Term frequency (TF): a measure of how often a term is found in a collection of documents. TF is combined with inverse document frequency (IDF) as a means of determining which documents are most relevant to a query. TF is sometimes also used to measure how often a word appears in a specific document (Source: SearchEngineDictionary.com) (see Chapter 3 keywords). Term length: the number of characters in a term (see Chapter 3 keywords). Text ad: advertisement using text-based hyperlinks (Source: Marketing Terms.com) (see Chapter 4 ads). Textual ad impressions: the delivery of a text-based advertisement to a browser. To compensate for slow Internet connections, visitors may disable “auto load images” in their graphical browser. When they reach a page that contains an advertisement, they see a marker and the advertiser’s message in text format in place of the graphical ad. Additionally, if a user has a text-only browser, only textual ads are delivered and recorded as textual ad impressions (Source: IAB) (see Chapter 7 analytics). The Google Golden Triangle: triangle that extends from the top of the results over to the top of the first result, then down to a point on the left side at the bottom of the “above the fold” visible results where most searchers examine when looking at a SERP (see Chapter 4 ads). Three-hit theory: a theory that proposes that the optimum number of exposures to an advertisement to induce learning is three: one to gain consumers’ awareness, a second to show the relevance of the product, and a third to show its benefits (see Chapter 4 ads). Time spent: the amount of elapsed time from the initiation of a visit to the last audience activity associated with that visit. Time spent should represent the activity of a single cookie browser or user for a single access session to the Web site or property (Source: IAB) (see Chapter 7 analytics). Time-to-convert: is calculated as the period from when a visitor clicks on an ad to when the visitor completes a purchase [2] (see Chapter 7 analytics). Title tag: an HTML meta tag with text describing a specific Web page. The title tag should contain strategic keywords for the page, because many search engines pay special attention to the title text when indexing pages. The title tag should also make sense to humans because it is usually the text link to the page displayed in search engine results (Source: Search Engine Watch) (see Chapter 2 model). Touch point: an opportunity to interact with a consumer in a buying cycle when consumers are open to influence (see Chapter 5 customers). Tracking: measuring the effectiveness of a campaign by collecting and evaluating statistics (Source: Quirk) (see Chapter 7 analytics).

Glossary

269

Trademarks: distinctive symbols, pictures, or words that identify a specific product or service, received through registration with the U.S. Patent & Trademark Office. Tier I search engines generally prohibit the use of trademarks in advertisements if the bidder is not the legal owner (Source: modified from SEMPO) (see Chapter 6 BAM!). Traffic: number of hits or visits a Web site receives during, usually, a twenty-fourhour period. Retailing: Number of shoppers that pass through a shopping area, mall, or store during the business hours. Refers to the number of visitors a Web site receives. It can be determined by examination of Web logs (Source: SEMPO) (see Chapter 7 analytics). Traffic analysis: the process of analyzing traffic to a Web site to understand what the visitors are searching for and what is driving traffic to a site (Source: SEMPO) (see Chapter 7 analytics). Unduplicated audience: the number of unique individuals exposed to a specified domain, page, or ad in a specified time period (Source: IAB) (see Chapter 6 BAM!). Uniform Resource Locator (URL): location of a resource on the Internet. A means of identifying an exact location on the Internet (Source: modified from Marketing Terms.com and WebTrends) (see Chapter 2 model). Unique selling proposition (USP): what makes one’s product or service better, or different, from the competition (see Chapter 6 BAM!). Unique user: unique individual or browser that either has accessed a site (see unique visitor) or has been served unique content and/or ads such as e-mail, newsletters, interstitials, and pop-under ads. Unique users can be identified by user registration or cookies. Reported unique users should filter out bots. See http://www.iab.net for ad campaign measurement guidelines (Source: IAB) (see Chapter 7 analytics). Unique visitor: a unique user who accesses a Web site within a specific time period. See unique user (Source: IAB) (see Chapter 7 analytics). Unique visitors (UV): refers to a measure captured by some Web analytics solutions that track the interaction a single user has with a Web site over time (Source: WebTrends) (see Chapter 7 analytics). Universal search: also known as blended or federated search results. Universal search pulls data from multiple databases to display on the same page. Results can include images, videos, and results from specialty databases like maps and local information, product information, or news stories (Source: Search Engine Watch) (see Chapter 2 model). Universe: total population of audience being measured (Source: IAB) (see Chapter 7 analytics). User: an individual with access to the Web (Source: IAB) (see Chapter 7 analytics). User agent: fields in an extended Web server log file identifying the browser and platform used by a visitor (Source: WebTrends) (see Chapter 2 model). User agent string: a field in a server log file that identifies the specific browser software and computer operating system making the request (Source: IAB) (see Chapter 2 model).

270

Glossary

User-centric measurement: Web audience measurement based on the behavior of a sample of Web users (Source: IAB) (see Chapter 7 analytics). User session: a period of activity (all hits) for one user of a Web site. A unique user is determined by the IP address or cookie. Typically, a user session is terminated when a user is inactive for more than thirty minutes (Source: WebTrends) (see Chapter 7 analytics). Value propositions: a customer value proposition is the sum total of benefits a customer is promised to receive in return for his or her custom and the associated payment (or other value transfer). A customer value proposition is what is promised by a company’s marketing and sales efforts and then fulfilled by its delivery and customer service processes (Source: SEMPO) (see Chapter 6 BAM!). View: often used as a synonym for impression (Source: IAB) (see Chapter 7 analytics). Viewer: person viewing content or ads on the Web. There is currently no way to measure viewers (Source: IAB) (see Chapter 7 analytics). Visit: a single continuous set of activity attributable to a cookie browser or user (if registration-based or a panel participant) resulting in one or more pulled text and/or graphics downloads from a site. A visit is an interaction a unique visitor has with a Web site over a specified period of time or activity. In most cases, if a visitor has left a site or has not executed a click-within thirty minutes, the visit session will terminate (Source: modified from IAB and WebTrends) (see Chapter 7 analytics). Visit duration: the length of time the visitor is exposed to a specific ad, Web page, or Web site during a single session (Source: IAB) (see Chapter 7 analytics). Visitor: individual or browser that accesses a Web site within a specific time period (Source: IAB) (see Chapter 7 analytics). Visitor session: interaction by a site visitor. The session ends when the visitor leaves the site (Source: WebTrends) (see Chapter 7 analytics). Wear-in: pertains to the notion that consumers often must be exposed to an ad more than once before the ad has any discernible positive effects (see Chapter 4 ads). Wear-out: pertains to the notion that after consumers have been exposed to an ad repeatedly, the ad may lose its effectiveness and may actually produce negative effects (see Chapter 4 ads). Web 2.0: a phrase that refers to a supposed second generation of Internet-based services. These usually include tools that let people collaborate and share information online, such as social networking sites, wikis, communication tools, and folksonomies (Source: Search Engine Watch) (see Chapter 2 model). Web analytics: site analytics essential to the success of any Web site. They provide you with information detailing how visitors are interacting with your site as well as how successful your supporting eMarketing techniques are on your site’s performance. Data for the analysis is mined using specialized software (we use

Glossary

271

ClickTracks!). Site analytics provide you with a comprehensive and insightful analysis of your Web site as well as an insight into what needs to be done to ensure even greater success (Source: Quirk) (see Chapter 7 analytics). Web page: an html, pdf, or other formatted single page on a Web site (see Chapter 2 model). Web record: all the information a search engine can display about a particular Web page in response to a query. In other words, search engines do not index actual pages. When a page is “indexed,” the search engine adds a snapshot-like “Web record” to its index. The Web record contains only the information the search engine is interested in (content) rather than the entire page. The contents of Web records obviously differ from one search engine to another, depending on what each search engine considers important to rank pages accurately (Source: SearchEngineDictionary.com) (see Chapter 7 analytics). Web server logs: most Web server software, and all good Web analytics packages, keeps a running count of all search terms used by visitors to your site. These running counts are kept in large text files called Log Files or Web Server Logs, useful for developing and refining PPC campaign keyword lists (Source: SearchEngineDictionary. com) (see Chapter 7 analytics). Web site: the virtual location (domain) for an organization’s or individual’s presence on the Web (Source: IAB) (see Chapter 2 model). Weighting: the technique search engines use to compare the relevance of different documents to a query. Search engines effectively “weigh” different pages based on things like the occurrence of keywords in the title in order to list documents in order from most to least relevant (Source: SearchEngineDictionary.com) (see Chapter 2 model). What if: a type of analysis that allows an end-user to pose hypothetical situations against their data to model or predict outcomes (Source: WebTrends) (see Chapter 7 analytics). Word-of-mouth: information that is passed between people, as opposed to messages from a company to people (Source: Quirk) (see Chapter 6 BAM!). Year over year (YOY): the means of comparing data from one year to the next. For example, to compare online holiday retail revenue from last year to this year (see Chapter 6 BAM!). Yield: the percentage of clicks versus impressions on an ad within a specific page. Also called ad click rate (Source: IAB) (see Chapter 6 BAM!). Yield management: yield and revenue management is the process of understanding, anticipating, and influencing advertiser and consumer behavior to maximize profits through better selling, pricing, packaging, and inventory management while delivering value to advertisers and site users (Source: IAB) (see Chapter 6 BAM!). Zipf’s principle of least effort: an information-seeking client will tend to use the most convenient search method (see Chapter 3 keywords).

272

Glossary References

[1] Johnson, S. 1755. “Johnson, Preface to the Dictionary.” In A Dictionary of the English Language. London: Johnson. Retrieved April 4, 2011, from http://ethnicity.rutgers.edu/~jlynch/Texts/preface.html [2] Brooks, N. 2006. “Repeat Search Behavior: Implications for Advertisers.” Bulletin of the American Society for Information Science and Technology, vol. 32(2), pp. 16–17.

Index

3 Cs, 131, 140–141 4 Ps, 130–131 7 Ps, 131, 140–141 8 Life Forces, 125 80–20 rule, 51, 136 A/B testing, 164–165 above the fold, 3, 21, 61 accretion, 159–160 achieve, 6, 25, 111, 124, 196 Action, Location, Price and Quality (ALPQ) terms, 69 ad copy, ix, 24, 61, 138, 140, 183–184, 207 ad rank, 74, 77–78, 178 advertising agency, 61, 122 advertising blockage, 120 AdWords, 14–15, 18, 180–181, 185 aesthetic sensations, 125 affiliation, 124 affordances, 2, 37, 130 aggress, 124 AIDA model, 94 allocation mechanism, 178 AltaVista, 13, 21, 38, 44 American Marketing Association, 139, 152 analysis of variances, 165 Anomalous States of Knowledge, 43 AOL Time Warner, 21 Asimov, Isaac, ix, 47, 96 attention, 5, 28, 55, 61, 68, 72, 116, 121–122, 124–126, 133–134, 153, 203, 205 Aucnet, 179 Auction theory, 180, 182, 210 autonomy, 125 Back of napkin calculations, 195 Baidu, 179 Bailey, P., 116 BAM framework, 140

band wagon effect, 114 Banister, Scott, 11 banner ads, 10–11, 19 Battelle, John, 31 A Beautiful Mind, 197 behavior, 33–38, 44–45, 47–49, 54, 63, 66–67, 70–72, 74, 80–82, 85–87, 94, 99, 101, 115, 151, 155–161, 168, 170, 189, 196, 210–213, 220, 222, 224 behaviorism, 156–157, 170–171, 210, 213 behaviors, x, xi, 34–36, 38, 42–43, 45, 49, 55, 62, 71, 74–75, 86–88, 94, 99, 114–115, 152, 156–159, 161–163, 167, 171, 210–212, 221–222, 226 below the fold, 21, 43 Bernbach, Bill, 61 Bhatia, Sabeer, 134 bid, xxi, 4–5, 12, 14, 19–20, 39, 119–120, 141, 170, 178–182, 184–200, 203, 209 Bierbaum, E. G., 71 biologically programmed desires, 125 The Black Swan, 218 Bloom’s Taxonomy, 96 Borden, Neil H., 131 bounded rationality, 98, 100 Boyce, Rick, 10 brand, 6, 14–15, 25, 69–70, 74, 95, 103, 111–122, 126–127, 129–130, 140–142, 144, 201, 207, 221, 223, 225 brand advertising, 126 Brand attitude, 116 brand awareness, 113 brand equity, 114 brand familiarity, 116 brand image, 1, 14–15, 70, 103, 112–114, 117, 120, 141 Brand recall, 114, 117 Brand recognition, 113, 117 Brand relationship, 114–115, 117

273

274

Index

Brand trust, 116–117 branded keyphrases, 119–120, 141, 183, 187 branded terms, 41, 69–70, 186 branding, xiii, 16, 65, 69, 103, 106, 111–114, 116–118, 120–121, 126, 128–129, 131, 135, 140–142, 149, 171, 177, 190, 199, 203, 207–209, 213, 227 Brewer, Jeffrey, 11 Brin, Sergey, 206, 217–218 Broder, Andrei, 44 Brooks, Nico, 76–77 Bullington, Brett, 12 butterfly effect, 205 buying decision, 98–99, 130 buying funnel, 86, 93–98, 101, 103–106, 129–130, 210, 213 Capitani, 74 Caples, John, 127 CA$HVERTISING, 125 causation, 153 caveat emptor, 179 chaos theory, 204 check-in applications, 224 choice set, 71, 79, 94, 120, 130 Choice uncertainty, 99 classic advertising appeals, 124 click fraud, 167–168, 170, 221 Click potential, 76 clickthrough lift, 124 click-through rate, 24, 74–75, 178, See€clickthrough rate, 14–15 The Cluetrain Manifesto, 129 Commercial Alert, 21 communication process, 32–33, 36, 54, 86, 101–103, 105–106, 111, 207, 210, 213 communication theory, 86 complexity theory, 204 comScore, 152 concept of chunking, 42 concept of technological innovation, 5 consumer behavior, xiii, 86, 89, 94, 96, 98, 101, 103, 105–106, 129 consumer buying behavior, 98, 103 consumer buying process, 94, 98, 100–101, 104, 106 consumer decision making, 86, 93–95, 101, 105, 208, 213 consumer purchasing behavior, 86 consumer search process, 48, 90, 93, 98 consumer searching, 41, 47, 63, 86–87, 90, 93, 95, 98–99, 210 consumer searching behavior, 41, 86, 95, 210 content targeting, 19

context, ix, x, xiii, xix, xx, xxi, 1, 11, 32–33, 36, 43, 69, 86, 88, 91–92, 97, 100–103, 106, 112, 114–115, 119, 126–128, 131, 157, 159–164, 166, 177, 187, 212, 217, 220, 224, 226 contextual advertising, xii, 19, 225 Conversion potential, 76 Corporate branding, 112 Correlation, 153 Credence goods, 39–40 creditability, 150 Culliton, James, 131 curiosity, i, ix, x, xiv, 46, 125 Customer brand image, 120 customer market segmentation, 120 Database of Intentions, 31 dayparting, 184, 186 Delhagen, Kate, 12 determinants, 92–93, 98, 118 Direct Hit Technologies, 21 direct response, 126 direct response advertising, 126 Doc Seals, 129 dominate, 125 east, 22, 24, 72 ebay, 179 Ebbinghaus, H., 74 economic theory, 49, 91 effectiveness, 24, 35, 113, 118, 145, 149, 151, 159, 170, 180, 210 efficiency, 62, 151, 170, 180, 210 empirical methods, xii erosion, 159–160 escape, 125 Esch, F. R., 112, 114–115 ethics of marketing, 139 ethogram, 158, 167 Evison, Rufus, 163 Excite, 12, 38 Experience goods, 39 external information search, 88 exteroceptors, 35, 63 eye tracking study, 72–73 Federal Trade Commission, 21 five forces, 136 five levels to a product, 138 Florida, 23 The Foundation Trilogy, 47 Fowles, J., 124 Fowles, R. B., 124 fractional pricing, 133 freemium model, 136 free-riding, 167

Index frequency of purchase, 98 fundamental theorem of demand, 91 game theory, 87, 171, 179–180, 196–197, 211 Geddes, Brad, 18 general systems theory, 204–205 Generalized Second Price auction, 180–181, 187–188 geo-location software, 220 goal of advertising, 121 Golden Ratio, 72 Golden Rule, 167 Golden Triangle, 72 GOMCHA. See€Google Online Marketing Challenge Good wine needs no bush, 127 Google, 2, 14–16, 18–19, 22–23, 81, 111, 119, 177, 179–181, 185–186, 191, 200, 206, 213, 217 Google Dance, 23 Google Golden Triangle, 72 Google Online Marketing Challenge, 19 GoTo.com, 10–13, 170 Gross, Bill, 9, 11 GSP. See€Generalized Second-Price auction guidance, xv, 124 Hawking, D., 116 Heisenberg’s uncertainty principle, 160 Hick-Hyman Law, 70–72, 211, 213 Hoque, A. Y., 75 Hotchkiss, Gord, 118 hotel problem, 163 Hotmail, 134 Hotwired, 10 human information behavior, 34, 36–37, 45, 55, 62, 211 human information processing, 35–36, 211 Hume’s Problem of Induction, 218 Hunt, S. D., 116 Hunter, Lee, 19 IdeaLab, 11 imperfect information, 179, 194 impression, 12, 14, 24, 75–77, 133, 209 impulse buying, 93, 97–98 income effect, 91 information access, 54–55, 70, 72 information acquisition, 35, 63 information asymmetry, 63–64 information foraging, 42, 44, 63, 66–67, 70, 72, 80, 96, 213 information foraging theory, 42, 67, 70 information imbalance, 63–64 information load, 63

275

information obtainability, 42–43, 49, 70–71, 211, 213 information overload, 68 information processing theory, 65, 94, 96 information retrieval, 2, 20, 37, 51, 70–71, 154, 211 information scent, 66–67 information science, xiii, 14, 35, 71, 87 information searching, 20, 37, 211 information theory, 42, 92 informational, xi, 44–46, 64, 93, 96 informivore, 66 Infoseek, 38 Intangible content, 131 internal information search, 88 Internet television, 224 iProspect, xvi, 167 iWon, 21 Jansen, Bernard J., 20, 44, 113–114, 116, 118, 158 Johnson, Samuel, 229 Kamangar, Salar, 181 key drivers of marketing, 128 key performance indicators, 24. See€key performance indicators Knowledge uncertainty, 99 known-unknown and aware-unaware, 150 Kotler, P., 128, 138 Kraatz, Mark, 12 La Gazette de France, 122 law of diminishing marginal returns, 50 law of probability, 165 Levine, Rick, 129 Levinson, Danny, 44 Lewis, E. St. Elmo, 94, 96 light-of-day test, 167 local deal websites, 224 Locke, Christopher, 129 Log analysis, 151 Lohse, G. L., 75 LookSmart, 21 Lun, Ts’ai, xii Lycos, 12, 21 Magical Number Seven, Plus or Minus Two, 42 magnitude, 153 marketing concept, 128 marketing mix, 131, 137 marketing research, 72, 149–150, 152 Maslow’s hierarchy of needs, 96 mass media, 34, 50, 88, 106, 123, 134 Mathur, Rajive, 12 Matthew Effect, 15

276

Index

Mayer, Marissa, 111 McBryan, Oliver, 10 McCarthy, J. E., 131 McNamara fallacy, 154 measure, 153 Measurement, 149, 153, 171, 209–210, 212 Meta-data, 24 metrics, ix, 12, 24, 26–27, 31, 126, 137, 153–154, 159, 171, 203, 221, 226 Michael H. Hart, 206 microblogging, 221 micro-payments, 224 Microsoft, xvi, 13, 21, 179, 213 Miller, Geroge A., 42 mobile apps, 221, 223–224 mobile technology, 222 Moore’s Law, 41 morality of the marketplace, 167 Morgan, R. M., 116 motives, 92–93 Murphy, Jamie, 19 Mustang, Ford, 124 Nash equilibrium, 196–198, 211, 213 navigational, 2, 44–45, 89, 96, 213, 223–224 Nelson, Paul, 39 Nielsen, Arthur, 152 Nielsen BuzzMetrics, 152 Nielsen Company, 152 Nielsen//NetRatings, 152 Nielsen ratings, 152 the normal distribution, 50 Norman, Don, 74 north, 22, 24, 190 nurture, 124 observer bias, 161 observer effect, 161 Ogilvy, David, 85 Onsale, 179 OpenText, 9, 11–12, 15 outcomes, 20, 47, 92–93, 100, 113, 115–116, 128, 150 Overture, 13–15, 179 P&G, 126 Page, Larry, 206 Palmer, Volney B., 122 papyrus, xii Pareto, Vilfredo, 51 Parisian Love, 186 Park, Daehee, 19 pay-for-impression, 19 pay-per-action, 19 pay-per-call, 19 pay-per-click, x, 3–4, 14, 19

Pedersen, Jan, 44 Pemberton, J. M., 70 Penniman, D., 151 Perception, 66, 117 perceptual process, 65 perfect information, 179–180, 184, 189, 197 personalization, 184, 226 Persuasive communication, 122 Pirolli, Pete, 44 Popper, Karl, 203 position impact, 74 positioning advertising, 126 power law, 49–55, 91, 104, 136, 211 prestige pricing, 133 primacy effect, 74–75 principle of least effort, 42–43, 49, 53–55, 58, 66–67, 70–72, 91, 96, 100, 114, 211, 213–214 privacy concerns, 223 Procter and Gamble, 11 prominence, 125 psychohistory, 47 Psychological needs, 125 quality score, 14, 184, 190–193, 196, 198, 200, 221 Quantum mechanics, 204 query length, 23, 41, 48–49 rational actor, 96, 100, 106 Real time content, 224 recency effect, 72, 74–75, 212–213 relevance, 10, 14, 20–21, 37, 64, 74, 76–77, 112–113, 118, 163, 184, 191, 211, 213 reliability, 141, 150, 164, 166, 171 Renaudot, Théophraste, 122 Resnick, Marc, 20, 118 RFM analysis, 104 right rail, 22 Rose, Dan, 44 Saracevic, Tefko, 44 satisficing, 42, 70, 92, 96 Schmidt, Eric, 177 Schrödinger’s cat paradox, 204 Schultz, C., 113, 116 Schwab, Victor O., 68, 100, 120, 165 screen real estate, 3–4, 21, 64, 120, 178, 199 search determinants, 92 Search Engine Marketing Professional Organization. See€SEMPO search engine optimization, 22 search engine results page. See€SERP Search goods, 39 search motives, 92 search outcomes, 93

Index

277

search theory, 38 Search, Experience and Credence. See€SEC SEC, 39–41 second price auction, 14, 200 Secondary data analysis, 161 See and Say, 123 SEMPO, 3 sensemaking, 43 sensory receptor, 63 serial position effect, 74–75, 213 SERP, 4, 17–26, 31, 50, 71–79, 90, 96, 103, 112, 116, 118, 124, 137, 140–141, 168–169, 177–179, 181–184, 189–191, 198–199, 208, 214, 222, 225 server logs, 154–155 Service branding, 112 session duration, 43 session length, 48–49 the seven words you can’t say on television, 32 sex, 124 Shannon, Claude, 42 SIGIR, xv, 2, 38, 173 signaling theory, 63–66, 75, 79–80, 211 signals, 35, 63–65, 67–70, 74, 79–80 Simon, Herbert, 68, 70 Simple Reaction Time, 63 Smith, Jack, 134 soap opera, 126 social media, 2, 225 south, 22, 24 Special Interest Group on Information Retrieval. See€SIGIR Spink, Amanda, 44, 158 sponsored search analytics, 142, 149, 151, 171, 210, 212, 226 sponsored search business model, 39 sponsored search process, xxi, 5–6, 9, 14, 18–20, 25–26, 101, 103, 111, 207 SSA. See€sponsored search analytics stakeholder analysis, 219 stakeholders, 219 streetlight effect, 159 substitution effect, 91 Sullivan, Danny, 9 Super Bowl ads, 185–186

theory of just noticeable differences, 65 third person effect, 123 Thomas, P., 11, 116 The Three Hit Theory, 64 Three Laws of Robotics, 96 Three Ws of Advertising, 120 trace data, 158–161, 166–167, 170–171, 212 transaction log, 151, 154–155, 159, 161–162, 166–167, 171 transaction log analysis, 154 transactional, 44–46, 96

tangible object, 131 Tested Advertising Methods, 127 Texas sharpshooter fallacy, 166

Zhang, Mimi, 113, 116 Zipf distribution, 53 Zipf’s Law, 52–53

ultimate relativism, x uncertainty, 39–43, 48–49, 54–55, 71, 86, 90, 98–100, 114, 212–213 uncertainty principle, 42–43, 160, 212 uncertainty reduction, 40–42 unobtrusive, 155, 159–162, 167, 171, 212 Unobtrusive methods, 155, 160, 212 user intent, 44–45, 47 validity, 150, 164, 166, 171 value, 167, 218–219 Varian, Hal, 181 Veach, Eric, 181 Vickrey auction, 180, 194, 196 Vickrey–Clarke–Groves. See€Vickrey–Clarke– Groves auction Vickrey–Clarke–Groves auction, 180 viral promotion, 134 Walter Thompson, J., 124 Wanamaker, John, 149 Watzlawick’s five axioms of communication, 101 Waugh, N., 74 web analytics, 149, 151, 154–155, 163, 209 web information searching, 38 Weinberger, David, 129 Weiner, Norbert, 42 Whitman, D. E., 125 Wilson, Tom, 71 wisdom of the crowd, 180 World-Wide Web Worm, 10 Yahoo!, 12–13, 15, 179, 213